We introduce a system to automatically manage photocopies made from copyrighted printed materials. The system monitors photocopiers to detect the copying of pages from copyrighted publications. Such activity is tallied for billing purposes. Access rights to the materials can be checked to prevent printing. Digital images of the copied pages are checked against a database of copyrighted pages. To preserve the privacy of the copying of non-copyright materials, only digital fingerprints are submitted to the image matching service. A problem with such systems is creation of the database of copyright pages. To facilitate this, our system maintains statistics of clusters of similar unknown page images along with copy sequence. Once such a cluster has grown to a sufficient size, a human inspector can determine whether those page sequences are copyrighted. The system has been tested with 100,000s of pages from conference proceedings and with millions of randomly generated pages. Retrieval accuracy has been around 99% even with copies of copies or double-page copies.

We previously created the HyperMeeting system to support a chain of geographically and temporally distributed meetings in the form of a hypervideo. This paper focuses on playback plans that guide users through the recorded meeting content by automatically following available hyperlinks. Our system generates playback plans based on users' interests or prior meeting attendance and presents a dialog that lets users select the most appropriate plan. Prior experience with playback plans revealed users' confusion with automatic link following within a sequence of meetings. To address this issue, we designed three timeline visualizations of playback plans. A user study comparing the timeline designs indicated that different visualizations are preferred for different tasks, making switching among them important. The study also provided insights that will guide research of personalized hypervideo, both inside and outside a meeting context.

New technology comes about in a number of different ways. It may come from advances in scientific research, through new combinations of existing technology, or by simply from imagining what might be possible in the future. This video describes the evolution of Tabletop Telepresence, a system for remote collaboration through desktop videoconferencing combined with a digital desk. Tabletop Telepresence provides a means to share paper documents between remote desktops, interact with documents and request services (such as translation), and communicate with a remote person through a teleconference. It was made possible by combining advances in camera/projector technology that enable a fully functional digital desk, embodied telepresence in video conferencing and concept art that imagines future workstyles.

While synchronous meetings are an important part of collaboration, it is not always possible for all stakeholders to meet at the same time. We created the concept of hypermeetings to support meetings with asynchronous attendance. Hypermeetings consist of a chain of video-recorded meetings with hyperlinks for navigating through the video content. HyperMeeting supports the synchronized viewing of prior meetings during a videoconference. Natural viewing behavior such as pausing generates hyperlinks between the previously recorded meetings and the current video recording. During playback, automatic link-following guided by playback plans present the relevant content to users. Playback plans take into account the user's meeting attendance and viewing history and match them with features such as speaker segmentation. A user study showed that participants found hyperlinks useful but did not always understand where they would take them. The study results provide a good basis for future system improvements.

Media Embedded Target, or MET, is an iconic mark printed in a blank margin of a page that indicates a media link is associated with a nearby region of the page. It guides the user to capture the region and thus retrieve the associated link through visual search within indexed content. The target also serves to separate page regions with media links from other regions of the page. The capture application on the cell phone displays a sight having the same shape as the target near the edge of a camera-view display. The user moves the phone to align the sight with the target printed on the page. Once the system detects correct sight-target alignment, the region in the camera view is captured and sent to the recognition engine which identifies the image and causes the associated media to be displayed on the phone. Since target and sight alignment defines a capture region, this approach saves storage by only indexing visual features in the predefined capture region, rather than indexing the entire page. Target-sight alignment assures that the indexed region is fully captured. We compare the use of MET for guiding capture with two standard methods: one that uses a logo to indicate that media content is available and text to define the capture region and another that explicitly indicates the capture region using a visible boundary mark.

We examine the use of clustering to identify selfies in a social media user's photos for use in estimating demographic information such as age, gender, and race. Faces are first detected within a user's photos followed by clustering using visual similarity. We define a cluster scoring scheme that uses a combination of within-cluster visual similarity and average face size in a cluster to rank potential selfie-clusters. Finally, we evaluate this ranking approach over a collection of Twitter users and discuss methods that can be used for improving performance in the future.

Embedded Media Markers (EMMs) are nearly transparent icons printed on paper documents that link to associated digital media. By using the document content for retrieval, EMMs are less visually intrusive than barcodes and other glyphs while still providing an indication for the presence of links. An initial implementation demonstrated good overall performance but exposed difficulties in guaranteeing the creation of unambiguous EMMs. We developed an EMM authoring tool that supports the interactive authoring of EMMs via visualizations that show the user which areas on a page may cause recognition errors and automatic feedback that moves the authored EMM away from those areas. The authoring tool and the techniques it relies on have been applied to corpora with different visual characteristics to explore the generality of our approach.

User-generated video from mobile phones, digital cameras, and other devices is increasing, yet people rarely want to watch all the captured video. More commonly, users want a single still image for printing or a short clip from the video for creating a panorama or for sharing. Our interface aims to help users search through video for these images or clips in a more efficient fashion than fast-forwarding or "scrubbing" through a video by dragging through locations on a slider. It is based on a hierarchical structure of keyframes in the video, and combines a novel user interface design for browsing a video segment tree with new algorithms for keyframe selection, segment identification, and clustering. These algorithms take into account the need for quality keyframes and balance the desire for short navigation paths and similarity-based clusters. Our user interface presents keyframe hierarchies and displays visual cues for keeping the user oriented while browsing the video. The system adapts to the task by using a non-temporal clustering algorithm when a the user wants a single image. When the user wants a video clip, the system selects one of two temporal clustering algorithm based on a measure of the repetitiveness of the video. User feedback provided us with valuable suggestions for improvements to our system.

This paper describes research activities at FX Palo Alto Laboratory (FXPAL) in the area of multimedia browsing, search, and retrieval. We first consider interfaces for organization and management of personal photo collections. We then survey our work on interactive video search and retrieval. Throughout we discuss the evolution of both the research challenges in these areas and our proposed solutions.

Embedded Media Markers, or simply EMMs, are nearly transparent iconic marks printed on paper documents that signify the existence of media associated with that part of the document. EMMs also guide users' camera operations for media retrieval. Users take a picture of an EMM-signified document patch using a cell phone, and the media associated with the EMM-signified document location is displayed on the phone. Unlike bar codes, EMMs are nearly transparent and thus do not interfere with the document appearance. Retrieval of media associated with an EMM is based on image local features of the captured EMM-signified document patch. This paper describes a technique for semi-automatically placing an EMM at a location in a document, in such a way that it encompasses sufficient identification features with minimal disturbance to the original document.

Embedded Media Barcode Links, or simply EMBLs, are optimally blended iconic barcode marks, printed on paper documents, that signify the existence of multimedia associated with that part of the document content (Figure 1). EMBLs are used for multimedia retrieval with a camera phone. Users take a picture of an EMBL-signified document patch using a cell phone, and the multimedia associated with the EMBL-signified document location is displayed on the phone. Unlike a traditional barcode which requires an exclusive space, the EMBL construction algorithm acts as an agent to negotiate with a barcode reader for maximum user and document benefits. Because of this negotiation, EMBLs are optimally blended with content and thus have less interference with the original document layout and can be moved closer to a media associated location. Retrieval of media associated with an EMBL is based on the barcode identification of a captured EMBL. Therefore, EMBL retains nearly all barcode identification advantages, such as accuracy, speed, and scalability. Moreover, EMBL takes advantage of users' knowledge of a traditional barcode. Unlike Embedded Media Maker (EMM) which requires underlying document features for marker identification, EMBL has no requirement for the underlying features. This paper will discuss the procedures for EMBL construction and optimization. It will also give experimental results that strongly support the EMBL construction and optimization ideas.

An Embedded Media Marker (EMM) is a transparent mark printed on a paper document that signifies the availability of additional media associated with that part of the document. Users take a picture of the EMM using a camera phone, and the media associated with that part of the document is displayed on the phone. Unlike bar codes, EMMs are nearly transparent and thus do not interfere with the document appearance. Retrieval of media associated with an EMM is based on image features of the document within the EMM boundary. Unlike other feature-based retrieval methods, the EMM clearly indicates to the user the existence and type of media associated with the document location. A semi-automatic authoring tool is used to place an EMM at a location in a document, in such a way that it encompasses sufficient identification features with minimal disturbance to the original document. We will demonstrate how to create an EMM-enhanced document, and how the EMM enables access to the associated media on a cell phone.

Photo libraries are growing in quantity and size, requiring better support for locating desired photographs. MediaGLOW is an interactive visual workspace designed to address this concern. It uses attributes such as visual appearance, GPS locations, user-assigned tags, and dates to filter and group photos. An automatic layout algorithm positions photos with similar attributes near each other to support users in serendipitously finding multiple relevant photos. In addition, the system can explicitly select photos similar to specified photos. We conducted a user evaluation to determine the benefit provided by similarity layout and the relative advantages offered by the different layout similarity criteria and attribute filters. Study participants had to locate photos matching probe statements. In some tasks, participants were restricted to a single layout similarity criterion and filter option. Participants used multiple attributes to filter photos. Layout by similarity without additional filters turned out to be one of the most used strategies and was especially beneficial for geographical similarity. Lastly, the relative appropriateness of the single similarity criterion to the probe significantly affected retrieval performance.

PACER is a gesture-based interactive paper system that supports fine-grained paper document content manipulation through the touch screen of a cameraphone. Using the phone's camera, PACER links a paper document to its digital version based on visual features. It adopts camera-based phone motion detection for embodied gestures (e.g. marquees, underlines and lassos), with which users can flexibly select and interact with document details (e.g. individual words, symbols and pixels). The touch input is incorporated to facilitate target selection at fine granularity,and to address some limitations of the embodied interaction, such as hand jitter and low input sampling rate. This hybrid interaction is coupled with other techniques such as semi-real time document tracking and loose physical-digital document registration, offering a gesture-based command system. We demonstrate the use of PACER in various scenarios including work-related reading, maps and music score playing. A preliminary user study on the design has produced encouraging user feedback, and suggested future research for better understanding of embodied vs. touch interaction and one vs. two handed interaction.

Browsing and searching for documents in large, online enterprise document repositories are common activities. While internet search produces satisfying results for most user queries, enterprise search has not been as successful because of differences in document types and user requirements. To support users in finding the information they need in their online enterprise repository, we created DocuBrowse, a faceted document browsing and search system. Search results are presented within the user-created document hierarchy, showing only directories and documents matching selected facets and containing text query terms. In addition to file properties such as date and file size, automatically detected document types, or genres, serve as one of the search facets. Highlighting draws the user’s attention to the most promising directories and documents while thumbnail images and automatically identified keyphrases help select appropriate documents. DocuBrowse utilizes document similarities, browsing histories, and recommender system techniques to suggest additional promising documents for the current facet and content filters.

Embedded Media Markers, or simply EMMs, are nearly transparent iconic marks printed on paper documents that signify the existence of media associated with that part of the document. EMMs also guide users' camera operations for media retrieval. Users take a picture of an EMMsignified document patch using a cell phone, and the media associated with the EMM-signified document location is displayed on the phone. Unlike bar codes, EMMs are nearly transparent and thus do not interfere with the document contents. Retrieval of media associated with an EMM is based on image local features of the captured EMMsignified document patch. This paper describes a technique for semi-automatically placing an EMM at a location in a document, in such a way that it encompasses sufficient identification features with minimal disturbance to the original document.

Browsing and searching for documents in large, online enterprise document repositories is an increasingly common problem. While users are familiar and usually satisfied with Internet search results for information, enterprise search has not been as successful because of differences in data types and user requirements. To support users in finding the information they need from electronic and scanned documents in their online enterprise repository, we created an automatic detector for genres such as papers, slides, tables, and photos. Several of those genres correspond roughly to file name extensions but are identified automatically using features of the document. This genre identifier plays an important role in our faceted document browsing and search system. The system presents documents in a hierarchy as typically found in enterprise document collections. Documents and directories are filtered to show only documents matching selected facets and containing optional query terms and to highlight promising directories. Thumbnail images and automatically identified keyphrases help select desired documents.

This paper presents a tool and a novel Fast Invariant Transform (FIT) algorithm for language independent e-documents access. The tool enables a person to access an e-document through an informal camera capture of a document hardcopy. It can save people from remembering/exploring numerous directories and file names, or even going through many pages/paragraphs in one document. It can also facilitate people’s manipulation of a document or people’s interactions through documents. Additionally, the algorithm is useful for binding multimedia data to language independent paper documents. Our document recognition algorithm is inspired by the widely known SIFT descriptor [4] but can be computed much more efficiently for both descriptor construction and search. It also uses much less storage space than the SIFT approach. By testing our algorithm with randomly scaled and rotated document pages, we can achieve a 99.73% page recognition rate on the 2188-page ICME06 proceedings and 99.9% page recognition rate on a 504-page Japanese math book.

Hyper-Hitchcock consists of three components for creating and viewing a form of interactive video called detail-on-demand video: a hypervideo editor, a hypervideo player, and algorithms for automatically generating hypervideo summaries. Detail-on-demand video is a form of hypervideo that supports one hyperlink at a time for navigating between video sequences. The Hyper-Hitchcock editor enables authoring of detail-on-demand video without programming and uses video processing to aid in the authoring process. The Hyper-Hitchcock player uses labels and keyframes to support navigation through and back hyperlinks. Hyper-Hitchcock includes techniques for automatically generating hypervideo summaries of one or more videos that take the form of multiple linear summaries of different lengths with links from the shorter to the longer summaries. User studies on authoring and viewing provided insight into the various roles of links in hypervideo and found that player interface design greatly affects people's understanding of hypervideo structure and the video they access.

We designed an interactive visual workspace, MediaGLOW, that supports users in organizing personal and shared photo collections. The system interactively places photos with a spring layout algorithm using similarity measures based on visual, temporal, and geographic features. These similarity measures are also used for the retrieval of additional photos. Unlike traditional spring-based algorithms, our approach provides users with several means to adapt the layout to their tasks. Users can group photos in stacks that in turn attract neighborhoods of similar photos. Neighborhoods partition the workspace by severing connections outside the neighborhood. By placing photos into the same stack, users can express a desired organization that the system can use to learn a neighborhood-specific combination of distances.

This demo introduces a tool for accessing an e-document by capturing one or more images of a real object or document hardcopy. This tool is useful when a file name or location of the file is unknown or unclear. It can save field workers and office workers from remembering/exploring numerous directories and file names. Frequently, it can convert tedious keyboard typing in a search box to a simple camera click. Additionally, when a remote collaborator cannot clearly see an object or a document hardcopy through remote collaboration cameras, this tool can be used to automatically retrieve and send the original e-document to a remote screen or printer.

Retail establishments want to know about traffic flow and patterns of activity in order to better arrange and staff their business. A large number of fixed video cameras are commonly installed at these locations. While they can be used to observe activity in the retail environment, assigning personnel to this is too time consuming to be valuable for retail analysis. We have developed video processing and visualization techniques that generate presentations appropriate for examining traffic flow and changes in activity at different times of the day. Taking the results of video tracking software as input, our system aggregates activity in different regions of the area being analyzed, determines the average speed of moving objects in the region, and segments time based on significant changes in the quantity and/or location of activity. Visualizations present the results as heat maps to show activity and object counts and average velocities overlaid on the map of the space.

DOTS (Dynamic Object Tracking System) is an indoor, real-time, multi-camera surveillance system, deployed in a real office setting. DOTS combines video analysis and user interface components to enable security personnel to effectively monitor views of interest and to perform tasks such as tracking a person. The video analysis component performs feature-level foreground segmentation with reliable results even under complex conditions. It incorporates an efficient greedy-search approach for tracking multiple people through occlusion and combines results from individual cameras into multi-camera trajectories. The user interface draws the users' attention to important events that are indexed for easy reference. Different views within the user interface provide spatial information for easier navigation. DOTS, with over twenty video cameras installed in hallways and other public spaces in our office building, has been in constant use for a year. Our experiences led to many changes that improved performance in all system components.

DOTS (Dynamic Object Tracking System) is an indoor, real-time, multi-camera surveillance system, deployed in a real office setting. DOTS combines video analysis and user interface components to enable security personnel to effectively monitor views of interest and to perform tasks such as tracking a person. The video analysis component performs feature-level foreground segmentation with reliable results even under complex conditions. It incorporates an efficient greedy-search approach for tracking multiple people through occlusion and combines results from individual cameras into multi-camera trajectories. The user interface draws the users' attention to important events that are indexed for easy reference. Different views within the user interface provide spatial information for easier navigation. DOTS, with over twenty video cameras installed in hallways and other public spaces in our office building, has been in constant use for a year. Our experiences led to many changes that improved performance in all system components.

A common video surveillance task is to keep track of people moving around the space being monitored. It is often difficult to track activity between cameras because locations such as hallways in office buildings can look quite similar and do not indicate the spatial proximity of the cameras. We describe a spatial video player that orients nearby video feeds with the field of view of the main playing video to aid in tracking between cameras. This is compared with the traditional bank of cameras with and without interactive maps for identifying and selecting cameras. We additionally explore the value of static and rotating maps for tracking activity between cameras. The study results show that both the spatial video player and the map improve user performance when compared to the camera-bank interface. Also, subjects change cameras more often with the spatial player than either the camera bank or the map, when available.

Video surveillance systems have become common across a wide number of environments. While these installations have included more video streams, they also have been placed in contexts with limited personnel for monitoring the video feeds. In such settings, limited human attention, combined with the quantity of video, makes it difficult for security personnel to identify activities of interest and determine interrelationships between activities in different video streams. We have developed applications to support security personnel both in analyzing previously recorded video and in monitoring live video streams. For recorded video, we created storyboard visualizations that emphasize the most important activity as heuristically determined by the system. We also developed an interactive multi-channel video player application that connects camera views to map locations, alerts users to unusual and suspicious video, and visualizes unusual events along a timeline for later replay. We use different analysis techniques to determine unusual events and to highlight them in video images. These tools aid security personnel by directing their attention to the most important activity within recorded video or among several live video streams.

Video surveillance requires keeping the human in the loop. Software can aid security personnel in monitoring and using video. We have developed a set of interface components designed to locate and follow important activity within security video. By recognizing and visualizing localized activity, presenting overviews of activity over time, and temporally and geographically contextualizing video playback, we aim to support security personnel in making use of the growing quantity of security video.

With the growing quantity of security video, it becomes vital that video surveillance software be able to support security personnel in monitoring and tracking activities. We have developed a multi-stream video player that plays recorded and live videos while drawing the users' attention to activity in the video. We will demonstrate the features of the video player and in particular, how it focuses on keeping the human in the loop and drawing their attention to activities in the video.

This chapter describes tools for browsing and searching through video to enable users to quickly locate video passages of interest. Digital video databases containing large numbers of video programs ranging from several minutes to several hours in length are becoming increasingly common. In many cases, it is not sufficient to search for relevant videos, but rather to identify relevant clips, typically less than one minute in length, within the videos. We offer two approaches for finding information in videos. The first approach provides an automatically generated interactive multi-level summary in the form of a hypervideo. When viewing a sequence of short video clips, the user can obtain more detail on the clip being watched. For situations where browsing is impractical, we present a video search system with a flexible user interface that incorporates dynamic visualizations of the underlying multimedia objects. The system employs automatic story segmentation, and displays the results of text and image-based queries in ranked sets of story summaries. Both approaches help users to quickly drill down to potentially relevant video clips and to determine the relevance by visually inspecting the material.

A video database can contain a large number of videos ranging from several minutes to several hours in length. Typically, it is not sufficient to search just for relevant videos, because the task still remains to find the relevant clip, typically less than one minute of length, within the video. This makes it important to direct the users attention to the most promising material and to indicate what material they already investigated. Based on this premise, we created a video search system with a powerful and flexible user interface that incorporates dynamic visualizations of the underlying multimedia objects. The system employes an automatic story segmentation, combines text and visual search, and displays search results in ranked sets of story keyframe collages. By adapting the keyframe collages based on query relevance and indicating which portions of the video have already been explored, we enable users to quickly find relevant sections. We tested our system as part of the NIST TRECVID interactive search evaluation, and found that our user interface enabled users to find more relevant results within the allotted time than other systems employing more sophisticated analysis techniques but less helpful user interfaces.

Hyper-Hitchcock is a hypervideo editor enabling the direct manipulation authoring of a particular form of hypervideo called "detail-on-demand video." This form of hypervideo allows a single link out of the currently playing video to provide more details on the content currently being presented. The editor includes a workspace to select, group, and arrange video clips into several linear sequences. Navigational links placed between the video elements are assigned labels and return behaviors appropriate to the goals of the hypervideo and the role of the destination video. Hyper-Hitchcock was used by students in a Computers and New Media class to author hypervideos on a variety of topics. The produced hypervideos provide examples of hypervideo structures and the link properties and behaviors needed to support them. Feedback from students identified additional link behaviors and features required to support new hypervideo genres. This feedback is valuable for the redesign of Hyper-Hitchcock and the design of hypervideo editors in general.

Organizing digital photograph collections according to events such as holiday gatherings or vacations is a common practice among photographers. To support photographers in this task, we present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structure or statistics of the photo collection. We present several variants of an automatic unsupervised algorithm to partition a collection of digital photographs based either on temporal similarity alone, or on temporal and content-based similarity. First, inter-photo similarity is quantified at multiple temporal scales to identify likely event clusters. Second, the final clusters are determined according to one of three clustering goodness criteria. The clustering criteria trade off computational complexity and performance. We also describe a supervised clustering method based on learning vector quantization. Finally, we review the results of an experimental evaluation of the proposed algorithms and existing approaches on two test collections.

Large video collections present a unique set of challenges to the search system designer. Text transcripts do not always provide an accurate index to the visual content, and the performance of visually based semantic extraction techniques is often inadequate for search tasks. The searcher must be relied upon to provide detailed judgment of the relevance of specific video segments. We describe a video search system that facilitates this user task by efficiently presenting search results in semantically meaningful units to simplify exploration of query results and query reformulation. We employ a story segmentation system and supporting user interface elements to effectively present query results at the story level. The system was tested in the 2004 TRECVID interactive search evaluations with very positive results.

The FXPAL photo application automatically organizes digital photo collections based on date, event, person, or place.

We present a search interface for large video collections with time-aligned text transcripts. The system is designed for users such as intelligence analysts that need to quickly find video clips relevant to a topic expressed in text and images. A key component of the system is a powerful and flexible user interface that incorporates dynamic visualizations of the underlying multimedia objects. The interface displays search results in ranked sets of story keyframe collages, and lets users explore the shots in a story. By adapting the keyframe collages based on query relevance and indicating which portions of the video have already been explored, we enable users to quickly find relevant sections. We tested our system as part of the NIST TRECVID interactive search evaluation, and found that our user interface enabled users to find more relevant results within the allotted time than those of many systems employing more sophisticated analysis techniques.

Presentation of FXPAL experiments in the 2004 TREC Video Retrieval Evaluations (TRECVID 2004). FXPAL participated in the shot boundary determination task, and the interactive search task.

As the size of the typical personal digital photo collection reaches well into the thousands or photos, advanced tools to manage these large collections are more and more necessary. In this demonstration, we present a semi-automatic approach that opportunistically takes advantage of the current state-of-the-art technology in face detection and recognition and combines it with user interface techniques to facilitate the task of labeling people in photos. We show how we use an accurate face detector to automatically extract faces from photos. Instead of having a less accurate face recognizer classify faces, we use it to sort faces by their similarity to a face model. We demonstrate our photo application that uses the extracted faces as UI proxies for actions on the underlying photos along with the sorting strategy to identify candidate faces for quick and easy face labeling.

With digital still cameras, users can easily collect thousands of photos. We have created a photo management application with the goal of making photo organization and browsing simple and quick, even for very large collections. A particular concern is the management of photos depicting people. We present a semi-automatic approach designed to facilitate the task of labeling photos with people that opportunistically takes advantage of the strengths of current state-of-the-art technology in face detection and recognition. In particular, an accurate face detector is used to automatically extract faces from photos while the less accurate face recognizer is used not to classify the detected faces, but to sort faces by their similarity to a chosen model. This sorting is used to present candidate faces within a user interface designed for quick and easy face labeling. We present results of a simulation of the usage model that demonstrate the improved ease that is achieved by our method.

We introduced detail-on-demand video as a simple type of hypervideo that allows users to watch short video segments and to follow hyperlinks to see additional detail. Such video lets users quickly access desired information without having to view the entire contents linearly. A challenge for presenting this type of video is to provide users with the appropriate affordances to understand the hypervideo structure and to navigate it effectively. Another challenge is to give authors tools that allow them to create good detail-on-demand video. Guided by user feedback, we iterated designs for a detail-on-demand video player. We also conducted two user studies to gain insight into people's understanding of hypervideo and to improve the user interface. We found that the interface design was tightly coupled to understanding hypervideo structure and that different designs greatly affected what parts of the video people accessed. The studies also suggested new guidelines for hypervideo authoring.

It is challenging to browse multimedia on mobile devices with small displays. We present MiniMedia Surfer, a prototype application for interactively searching a multimedia collection for video segments of interest. Transparent layers are used to support browsing subtasks: keyword query, exploration of results through keyframes, and playback of video. This layered interface smoothly blends the key tasks of the browsing process and deals with the small screen size. During exploration, the user can adjust the transparency levels of the layers using pen gestures. Details of the video segments are displayed in an expandable timeline that supports gestural interaction.

We present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structure or statistics of the photo collection. We present results for the algorithm based solely on temporal similarity, and jointly on temporal and content-based similarity. We also describe a supervised algorithm based on learning vector quantization. Finally, we include experimental results for the proposed algorithms and several competing approaches on two test collections.

We present a system that allows remote and local participants to control devices in a meeting environment using mouse or pen based gestures "through" video windows. Unlike state-of-the-art device control interfaces that require interaction with text commands, buttons, or other artificial symbols, our approach allows users to interact with devices through live video of the environment. This naturally extends our video supported pan/tilt/zoom (PTZ) camera control system, by allowing gestures in video windows to control not only PTZ cameras, but also other devices visible in video images. For example, an authorized meeting participant can show a presentation on a screen by dragging the file on a personal laptop and dropping it on the video image of the presentation screen. This paper presents the system architecture, implementation tradeoffs, and various meeting control scenarios.

To simplify the process of editing interactive video, we developed the concept of "detail-on-demand" video as a subset of general hypervideo. Detail-on-demand video keeps the authoring and viewing interfaces relatively simple while supporting a wide range of interactive video applications. Our editor, Hyper-Hitchcock, provides a direct manipulation environment in which authors can combine video clips and place hyperlinks between them. To summarize a video, Hyper-Hitchcock can also automatically generate a hypervideo composed of multiple video summary levels and navigational links between these summaries and the original video. Viewers may interactively select the amount of detail they see, access more detailed summaries, and navigate to the source video through the summary.

In this paper, we describe how a detail-on-demand representation for interactive video is used in video summarization. Our approach automatically generates a hypervideo composed of multiple video summary levels and navigational links between these summaries and the original video. Viewers may interactively select the amount of detail they see, access more detailed summaries, and navigate to the source video through the summary. We created a representation for interactive video that supports a wide range of interactive video applications and Hyper-Hitchcock, an editor and player for this type of interactive video. Hyper-Hitchcock employs methods to determine (1) the number and length of levels in the hypervideo summary, (2) the video clips for each level in the hypervideo, (3) the grouping of clips into composites, and (4) the links between elements in the summary. These decisions are based on an inferred quality of video segments and temporal relations those segments.

The FXPAL Photo Application is designed to faciliate the organization of digital images from digital cameras and other sources through automated organization and intuitive user interfaces.

We demonstrate the use of detail-on-demand hypervideo in interactive training and video summarization. Detail-on-demand video allows viewers to watch short video segments and to follow hyperlinks to see additional detail. The player for detail-ondemand video displays keyframes indicating what links are available at each point in the video. The Hyper-Hitchcock authoring tool helps users create hypervideo by automatically dividing video into clips that can be combined in a direct manipulation interface. Clips can be grouped into composites and hyperlinks can be placed between clips and composites. A summarization algorithm creates multi-level hypervideo summaries from linear video by automatically selecting clips and placing links between them.

Hypervideo is a form of interactive video that allows users to follow links to other video. A simple form of hypervideo, called "detail-on-demand video," provides at most one link from one segment of video to another, supporting a singlebutton interaction. Detail-on-demand video is well suited for interactive video summaries, because the user can request a more detailed summary while watching the video. Users interact with the video is through a special hypervideo player that displays keyframes with labels indicating when a link is available. While detail-on-demand summaries can be manually authored, it is a time-consuming task. To address this issue, we developed an algorithm to automatically generate multi-level hypervideo summaries. The highest level of the summary consists of the most important clip from each take or scene in the video. At each subsequent level, more clips from each take or scene are added in order of their importance. We give one example in which a hypervideo summary is created for a linear training video. We also show how the algorithm can be modified to produce a hypervideo summary for home video.

To simplify the process of editing interactive video, we developed the concept of "detail-on-demand" video as a subset of general hypervideo where a single button press reveals additional information about the current video sequence. Detail-on-demand video keeps the authoring and viewing interfaces relatively simple while supporting a wide range of interactive video applications. Our editor, Hyper-Hitchcock, builds on prior work on automatic analysis to find the best quality video clips. It introduces video composites as an abstraction for grouping and manipulating sets of video clips. Navigational links can be created between any two video clips or composites. Such links offer a variety of return behaviors for when the linked video is completed that can be tailored to different materials. Initial impressions from a pilot study indicate that Hyper-Hitchcock is easy to learn although the behavior of links is not immediately intuitive for all users.

With digital still cameras, users can easily collect thousands of photos. Our goal is to make organizing and browsing photos simple and quick, while retaining scalability to large collections. To that end, we created a photo management application concentrating on areas that improve the overall experience without neglecting the mundane components of such an application. Our application automatically divides photos into meaningful events such as birthdays or trips. Several user interaction mechanisms enhance the user experience when organizing photos. Our application combines a light table for showing thumbnails of the entire photo collection with a tree view that supports navigating, sorting, and filtering photos by categories such as dates, events, people, and locations. A calendar view visualizes photos over time and allows for the quick assignment of dates to scanned photos. We fine-tuned our application by using it with large personal photo collections provided by several users.

Existing hypertext systems have emphasized either the navigational or spatial expression of relationships between objects. We are exploring the combination of these modes of expression in Hyper-Hitchcock, a hypervideo editor. Hyper-Hitchcock supports a form of hypervideo called "detail-on-demand video" due to its applicability to situations where viewers need to take a link to view more details on the content currently being presented. Authors of detail-on-demand video select, group, and spatially arrange video clips into linear sequences in a two-dimensional workspace. Hyper-Hitchcock uses a simple spatial parser to determine the temporal order of selected video clips. Authors add navigational links between the elements in those sequences. This combination of navigational and spatial hypertext modes of expression separates the clip sequence from the navigational structure of the hypervideo. Such a combination can be useful in cases where multiple forms of inter-object relationships must be expressed on the same content.

We created an alternative approach to existing video summaries that gives viewers control over the summaries by selecting hyperlinks to other video with additional information. We structure such summaries as "detail-on-demand" video, a subset of general hypervideo in which at most one link to another video sequence is available at any given time. Our editor for such video, Hyper-Hitchcock, provides a workspace in which an author can select and arrange video clips, generate composites from clips and from other composites, and place links between composites. To simplify dealing with a large number of clips, Hyper-Hitchcock generates iconic representations for composites that can be used to manipulate the composite as a whole. In addition to providing an authoring environment, Hyper-Hitchcock can automatically generate multi-level hypervideo summaries for immediate use or as the starting point for author modification.

Hitchcock is a semi-automatic video editing system. This video shows users collaboratively authoring a home video.

FlySPEC is a video camera system designed for real-time remote operation. A hybrid design combines the high resolution possible using an optomechanical video camera, with the wide field of view always available from a panoramic camera. The control system integrates requests from multiple users with the result that each controls a virtual camera. The control system seamlessly integrates manual and fully automatic control. It supports a range of options from untended automatic to full manual control, and the system can learn control strategies from user requests. Additionally, the panoramic view is always available for an intuitive interface, and objects are never out of view regardless of the zoom factor. We present the system architecture, an information-theoretic approach to combining panoramic and zoomed images to optimally satisfy user requests, and experimental results that show the FlySPEC system significantly assists users in a remote inspection tasks.

We present a method for rapidly and robustly extracting audio excerpts without the overhead of speech recognition or speaker segmentation. An immediate application is to automatically augment keyframe-based video summaries with informative audio excerpts associated with the video segments represented by the keyframes. Short audio clips combined with keyframes comprise an extremely lightweight and Web-browsable interface for auditioning video or similar media, without using bandwidth-intensive streaming video or audio.

This paper presents a camera system called FlySPEC. In contrast to a traditional camera system that provides the same video stream to every user, FlySPEC can simultaneously serve different video-viewing requests. This flexibility allows users to conveniently participate in a seminar or meeting at their own pace. Meanwhile, the FlySPEC system provides a seamless blend of manual control and automation. With this control mix, users can easily make tradeoffs between video capture effort and video quality. The FlySPEC camera is constructed by installing a set of Pan/Tilt/Zoom (PTZ) cameras near a high-resolution panoramic camera. While the panoramic camera provides the basic functionality of serving different viewing requests, the PTZ camera is managed by our algorithm to improve the overall video quality that may affect users watching details. The video resolution improvements from using different camera management strategies are compared in the experimental section.

We present a framework, motivated by rate-distortion theory and the human visual system, for optimally representing the real world given limited video resolution. To provide users with high fidelity views, we built a hybrid video camera system that combines a fixed wide-field panoramic camera with a controllable pan/tilt/zoom (PTZ) camera. In our framework, a video frame is viewed as a limited-frequency representation of some "true" image function. Our system combines outputs from both cameras to construct the highest fidelity views possible, and controls the PTZ camera to maximize information gain available from higher spatial frequencies. In operation, each remote viewer is presented with a small panoramic view of the entire scene, and a larger close-up view of a selected region. Users may select a region by marking the panoramic view. The system operates the PTZ camera to best satisfy requests from multiple users. When no regions are selected, the system automatically operates the PTZ camera to minimize predicted video distortion. High-resolution images are cached and sent if a previously recorded region has not changed and the PTZ camera is pointed elsewhere. We present experiments demonstrating that the panoramic image can effectively predict where to gain the most information, and also that the system provides better images to multiple users than conventional camera systems.

To meet the diverse needs of business, education, and personal video users, the authors developed three visual interfaces that help identify potentially useful or relevant video segments. In such interfaces, keyframes-still images automatically extracted from video footage-can distinguish videos, summarize them, and provide access points. Well-chosen keyframes enhance a listing's visual appeal and help users select videos. Keyframe selection can vary depending on the application's requirements: A visual summary of a video-captured meeting may require only a few highlight keyframes, a video editing system might need a keyframe for every clip, while a browsing interface requires an even distribution of keyframes over the video's full length. The authors conducted user studies for each of their three interfaces, gathering input for subsequent interface improvements. The studies revealed that finding a similarity measure for collecting video clips into groups that more closely match human perception poses a challenge. Another challenge is to further improve the video-segmentation algorithm used for selecting keyframes. A new version will provide users with more information and control without sacrificing the interface's ease of use.

Hitchcock is a system to simplify the process of editing video. Its key features are the use of automatic analysis to find the best quality video clips, an algorithm to cluster those clips into meaningful piles, and an intuitive user interface for combining the desired clips into a final video. We conducted a user study to determine how the automatic clip creation and pile navigation support users in the editing process. The study showed that users liked the ease-of-use afforded by automation, but occasionally had problems navigating and overriding the automated editing decisions. These findings demonstrate the need for a proper balance between automation and user control. Thus, we built a new version of Hitchcock that retains the automatic editing features, but provides additional controls for navigation and for allowing users to modify the system decisions.

Hitchcock is a system that allows users to easily create custom videos from raw video shot with a standard video camera. In contrast to other video editing systems, Hitchcock uses automatic analysis to determine the suitability of portions of the raw video. Unsuitable video typically has fast or erratic camera motion. Hitchcock first analyzes video to identify the type and amount of camera motion: fast pan, slow zoom, etc. Based on this analysis, a numerical "unsuitability" score is computed for each frame of the video. Combined with standard editing rules, this score is used to identify clips for inclusion in the final video and to select their start and end points. To create a custom video, the user drags keyframes corresponding to the desired clips into a storyboard. Users can lengthen or shorten the clip without specifying the start and end frames explicitly. Clip lengths are balanced automatically using a spring-based algorithm.

We describe a genetic segmentation algorithm for video. This algorithm operates on segments of a string representation. It is similar to both classical genetic algorithms that operate on bits of a string and genetic grouping algorithms that operate on subsets of a set. For evaluating segmentations, we define similarity adjacency functions, which are extremely expensive to optimize with traditional methods. The evolutionary nature of genetic algorithms offers a further advantage by enabling incremental segmentation. Applications include video summarization and indexing for browsing, plus adapting to user access patterns.

We describe a genetic segmentation algorithm for image data streams and video. This algorithm operates on segments of a string representation. It is similar to both classical genetic algorithms that operate on bits of a string and genetic grouping algorithms that operate on subsets of a set. It employs a segment fair crossover operation. For evaluating segmentations, we define similarity adjacency functions, which are extremely expensive to optimize with traditional methods. The evolutionary nature of genetic algorithms offers a further advantage by enabling incremental segmentation. Applications include browsing and summarizing video and collections of visually rich documents, plus a way of adapting to user access patterns.

We present and interactive system that allows a user to locate regions of video that are similar to a video query. Thus segments of video can be found by simply providing an example of the video of interest. The user selects a video segment for the query from either a static frame-based interface or a video player. A statistical model of the query is calculated on-the-fly, and is used to find similar regions of video. The similarity measure is based on a Gaussian model of reduced frame image transform coefficients. Similarity in a single video is displayed in the Metadata Media Player. The player can be used to navigate through the video by jumping between regions of similarity. Similarity can be rapidly calculated for multiple video files as well. These results are displayed in MBase, a Web-based video browser that allows similarity in multiple video files to be visualized simultaneously.

NoteLook is a client-server system designed and built to support multimedia note taking in meetings with digital video and ink. It is integrated into a conference room equipped with computer controllable video cameras, video conference camera, and a large display rear video projector. The NoteLook client application runs on wireless pen-based notebook computers. Video channels containing images of the room activity and presentation material are transmitted by the NoteLook servers to the clients, and the images can be interactively and automatically incorporated into the note pages. Users can select channels, snap in large background images and sequences of thumbnails, and write freeform ink notes. A smart video source management component enables the capture of high quality images of the presentation material from a variety of sources. For accessing and browsing the notes and recorded video, NoteLook generates Web pages with links from the images and ink strokes correlated to the video.

We describe a media enriched conference room designed for capturing meetings. Our goal is to do this in a flexible, seamless, and unobtrusive manner in a public conference room that is used for everyday work. Room activity is captured by computer controllable video cameras, video conference cameras, and ceiling microphones. Presentation material displayed on a large screen rear video projector is captured by a smart video source management component that automatically locates the highest fidelity image source. Wireless pen-based notebook computers are used to take notes, which provide indexes to the captured meeting. Images can be interactively and automatically incorporated into the notes. Captured meetings may be browsed on the Web with links to recorded video.

When reviewing collections of video such as recorded meetings or presentations, users are often interested only in an overview or short segments of these documents. We present techniques that use automatic feature analysis, such as slide detection and applause detection, to help locate the desired video and to navigate to regions of interest within it. We built a web-based interface that graphically presents information about the contents of each video in a collection such as its keyframes and the distribution of a particular feature over time. A media player is tightly integrated with the web interface. It supports navigation within a selected file by visualiz-ing confidence scores for the presence of features and by using them as index points. We conducted a user study to refine the usability of these tools.

This paper describes a technique for automatically creating an index for handwritten notes captured as digital ink. No text recog-nition is performed. Rather, a dictionary of possible index terms is built by clustering groups of ink strokes corresponding roughly to words. Terms whose distribution varies significantly across note pages are selected for the index. An index page containing the index terms is created, and terms are hyper-linked back to their original location in the notes. Further, index terms occurring in a note page are highlighted to aid browsing.

This paper describes a method for finding segments in video-recorded meetings that correspond to presentations. These segments serve as indexes into the recorded meeting. The system automatically detects intervals of video that correspond to presentation slides. We assume that only one person speaks during an interval when slides are detected. Thus these intervals can be used as training data for a speaker spotting system. An HMM is automatically constructed and trained on the audio data from each slide interval. A Viterbi alignment then resegments the audio according to speaker. Since the same speaker may talk across multiple slide intervals, the acoustic data from these intervals is clustered to yield an estimate of the number of distinct speakers and their order. This allows the individual presentations in the video to be identified from the location of each presenter's speech. Results are presented for a corpus of six meeting videos.

In this paper, we describe a technique for dynamically grouping digital ink and audio to support user interaction in freeform note-taking systems. For ink, groups of strokes might correspond to words, lines, or paragraphs of handwritten text. For audio, groups might be a complete spoken phrase or a speaker turn in a conversation. Ink and audio grouping is important for editing operations such as deleting or moving chunks of ink and audio notes. The grouping technique is based on hierarchical agglomerative clustering. This clustering algorithm yields groups of ink or audio in a range of sizes, depending on the level in the hierarchy, and thus provides structure for simple interactive selection and rapid non-linear expansion of a selection. Ink and audio grouping is also important for marking portions of notes for subsequent browsing and retrieval. Integration of the ink and audio clusters provides a flexible way to browse the notes by selecting the ink cluster and playing the corresponding audio cluster.

Many techniques can extract information from an multimedia stream, such as speaker identity or shot boundaries. We present a browser that uses this information to navigate through stored media. Because automatically-derived information is not wholly reliable, it is transformed into a time-dependent "confidence score." When presented graphically, confidence scores enable users to make informed decisions about regions of interest in the media, so that non-interesting areas may be skipped. Additionally, index points may be determined automatically for easy navigation, selection, editing, and annotation and will support analysis types other than the speaker identification and shot detection used here.

This paper describes a technique for segmenting video using hidden Markov models (HMM). Video is segmented into regions defined by shots, shot boundaries, and camera movement within shots. Features for segmentation include an image-based distance between adjacent video frames, an audio distance based on the acoustic difference in intervals just before and after the frames, and an estimate of motion between the two frames. Typical video segmentation algorithms classify shot boundaries by computing an image-based distance between adjacent frames and comparing this distance to fixed, manually determined thresholds. Motion and audio information is used separately. In contrast, our segmentation technique allows features to be combined within the HMM framework. Further, thresholds are not required since automatically trained HMMs take their place. This algorithm has been tested on a video data base, and has been shown to improve the accuracy of video segmentation over standard threshold-based systems.

In this paper we describe a method for indexing and retrieval of multimedia data based on annotation and segmentation. Our goal is the retrieval of segments of audio and video suitable for inclusion in multimedia documents. Annotation refers to the association of text data with particular time locations of the media. Segmentation is the partitioning of continuous media into homogenous regions. Retrieval is performed over segments of the media using the annotations associated with the segments. We present two scenarios that describe how these techniques might be applied. In the first, we describe how excerpts from a video-taped usage study of a new device are located for inclusion in a report on the utility of the device. In the second, we show how sound bites from a recorded meeting are obtained for use in authoring a summary of the meeting.

As the concept of what constitutes a "content-based" search grows more mature, it becomes valuable for us to establish a clear sense of just what is meant by "content." Recent multimedia document retrieval systems have dealt with this problem by indexing across multiple indexes; but it is important to identify how such multiple indexes are dealing with multiple dimensions of a description space, rather than simply providing the user with more descriptors. In this paper we consider a description space for multimedia documents based on three "dimensions" of a document, namely context, form, and content. We analyze the nature of this space with respect to three challenging examples of multimedia search tasks, and we address the nature of the index structures that would facilitate how these tasks may be achieved. These examples then lead us to some general conclusions on the nature of multimedia indexing and the intuitions we have inherited from the tradition of books and libraries.

Dynomite is a portable electronic notebook for the capture and retrieval of handwritten and audio notes. The goal of Dynomite is to merge the organization, search, and data acquisition capabilities of a computer with the benefits of a paper-based notebook. Dynomite provides novel solutions in four key problem areas. First, Dynomite uses a casual, low cognitive overhead interface. Second, for content indexing of notes, Dynomite uses ink properties and keywords. Third, to assist organization, Dynomite's properties and keywords define views, presenting a subset of the notebook content that dynamically changes as users add new information. Finally, to augment handwritten notes with audio on devices with limited storage, Dynomite continuously records audio, but only permanently stores those parts highlighted by the user.

Dynomite is a portable electronic notebook that merges the benefits of paper note-taking with the organizational capabilities of computers. Dynomite incorporates four complementary features which combine to form an easy to use system for the capture and retrieval of handwritten and audio notes. First, Dynomite has a paper-like user interface. Second, Dynomite uses ink properties and keywords for content indexing of notes. Third, Dynomite's properties and keywords allows retrieval of specific ink and notes. The user is shown a view, or a subset of the notebook content, that dynamically changes as new information is added. Finally, Dynomite continuously records audio, but only permanently stores highlighted portions so that it is possible to augment handwritten notes with audio on devices with limited storage.

In this chapter, we discuss mixed-media access, an information access paradigm for multimedia data in which the media type of a query may differ from that of the data. This allows a single query to be used to retrieve information from data consisting of multiple types of media. In addition, multiple queries formulated in different media types can be used to more accurately specify the data to be retrieved. The types of media considered in this paper are speech, images of text, and full-length text. Some examples of metadata for mixed-media access are locations of keywords in speech and images, identification of speakers, locations of emphasized regions in speech, and locations of topic boundaries in text. Algorithms for automatically generating this metadata are described, including word spotting, speaker segmentation, emphatic speech detection, and subtopic boundary location. We illustrate the use of mixed-media access with an example of information access from multimedia data surrounding a formal presentation.

S.W. Smoliar, J.D. Baker, T. Nakayama, and L. Wilcox,

Online digital audio is a rapidly growing resource, which can be accessed in rich new ways not previously possible. For example, it is possible to listen to just those portions of a long discussion which involve a given subset of people, or to instantly skip ahead to the next speaker. Providing this capability to users, however, requires generation of necessary indices, as well as an interface which utilizes these indices to aid navigation. We describe algorithms which generate indices from automatic acoustic segmentation. These algorithms use hidden Markov models to segment audio into segments corresponding to different speakers or acoustics classes (e.g. music). Unsupervised model initialization using agglomerative clustering is described, and shown to work as well in most cases as supervised initialization. We also describe a user interface which displays the segmentation in the form of a timeline, which tracks for the different acoustic classes. The interface can be used for direct navigation through the audio.