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.

Our analysis and visualization tools use 3D building geometry to support surveillance tasks. These tools are part of DOTS, our multicamera surveillance system; a system with over 20 cameras spread throughout the public spaces of our building. The geometric input to DOTS is a floor plan and information such as cubicle wall heights. From this input we construct a 3D model and an enhanced 2D floor plan that are the bases for more specific visualization and analysis tools. Foreground objects of interest can be placed within these models and dynamically updated in real time across camera views. Alternatively, a virtual first-person view suggests what a tracked person can see as she moves about. Interactive visualization tools support complex camera-placement tasks. Extrinsic camera calibration is supported both by visualizations of parameter adjustment results and by methods for establishing correspondences between image features and the 3D model.

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.

We describe a new interaction technique that allows users to control nonlinear video playback by directly manipulating objects seen in the video. This interaction technique is simi-lar to video "scrubbing" where the user adjusts the playback time by moving the mouse along a slider. Our approach is superior to variable-scale scrubbing in that the user can con-centrate on interesting objects and does not have to guess how long the objects will stay in view. Our method relies on a video tracking system that tracks objects in fixed cameras, maps them into 3D space, and handles hand-offs between cameras. In addition to dragging objects visible in video windows, users may also drag iconic object representations on a floor plan. In that case, the best video views are se-lected for the dragged objects.

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.

The MediaMetro application provides an interactive 3D visualization of multimedia document collections using a city metaphor. The directories are mapped to city layouts using algorithms similar to treemaps. Each multimedia document is represented by a building and visual summaries of the different constituent media types are rendered onto the sides of the building. From videos, Manga storyboards with keyframe images are created and shown on the façade; from slides and text, thumbnail images are produced and subsampled for display on the building sides. The images resemble windows on a building and can be selected for media playback. To support more facile navigation between high overviews and low detail views, a novel swooping technique was developed that combines altitude and tilt changes with zeroing in on a target.

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.

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.

We developed a novel technique for creating visually pleasing collages from photo regions. The technique is called "stained glass" because the resulting collage with irregular shapes is reminiscent of a stained glass window. The collages reuse photos in novel ways to present photos with faces that can be printed, included in Web pages, or shared via email. The poster describes the requirements for creating stained glass visualizations from photos of faces, our approach for creating face stained glass, and techniques used to improve the aesthetics and flexibility of the stained glass generation. Early user feedback with face stained glass have been very positive.

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.

Information sharing, computation and social interaction are main features of the Web that has enabled online communities to abound and flourish. However, this trend has not been coupled with the development of cues and browsing mechanisms for the social space. On the flip side, active contributors to social spaces (i.e., Web communities) lack the means to present a public face to visitors that can be important for social organizations. Social browsers that combine social visualization and tools can enable newcomers and visitors to view and explore information and patterns. We present two social browsers for two Web communities. The CHIplace People browser provides an abstract graphical view of the CHIplace community based on the self-described work roles of its membership. The Portkey eTree browser uses a life-like tree ecosystem metaphor to reflect the people, activities and discussions occurring on the Portkey Web site.

This paper presents a method for creating highly condensed video summaries called Stained-Glass visualizations. These are especially suitable for small displays on mobile devices. A morphological grouping technique is described for finding 3D regions of high activity or motion from a video embedded in x-y-t space. These regions determine areas in the keyframes, which can be subsumed in a more general geometric framework of germs and supports: germs are the areas of interest, and supports give the context. Algorithms for packing and laying out the germs are provided. Gaps between the germs are filled using a Voronoi-based method. Irregular shapes emerge, and the result looks like stained glass.

FX Palo Alto Laboratory provides multimedia and information technology research for the Fuji Xerox corporation based in Tokyo, Japan. FXPAL's mission is to help Fuji Xerox with a digital information technology infrastructure to support services in Fuji Xerox's Open Office Frontier. Our research spans interactive media, immersive conferencing, social computing, mobile and adaptive computing, natural language inquiry, and emerging technologies such as quantum computing and bioinformatics. Our research methods combine determining user needs, inventing new technologies, building prototype systems, informing professional communities, and transferring technology to Fuji Xerox. The physical distance between our laboratory and our parent company makes it natural for us to research problems with collaborations across time zones and cultures. To address these problems, to test our ideas, and to prepare for technology transfers, we actively create prototype systems for interactive media, immersive conferencing, and social and mobile computing. We also foster collaboration with our Japanese colleagues through a combination of face-to-face visits and both synchronous and asynchronous remote communication.

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.

Blurring the boundary between the digital and physical in social activity spaces helps blend - and motivate - online and face-to-face community participation. This paper discusses two experimental installations of large screen displays at conferences - CHI 2002 and CSCW 2002. The displays offered a window in the conference arena onto online community information.