We present an investigation of interaction models for slideshow applications in a multi-display environment. Three models are examined: Direct Manipulation, Billiard Ball, and Flow. These concepts can be demonstrated by the ModSlideShow prototype, which is designed as a configurable modular display system where each display unit communicates with its neighbors and fundamental operations that act locally can be composed to support the higher level interaction models. We also describe the gesture input scheme, animation feedback, and other enhancements.

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.

We present the iterative design of Momento, a tool that provides integrated support for situated evaluation of ubiquitous computing applications. We derived requirements for Momento from a user-centered design process that included interviews, observations and field studies of early versions of the tool. Motivated by our findings, Momento supports remote testing of ubicomp applications, helps with participant adoption and retention by minimizing the need for new hardware, and supports mid-to-long term studies to address infrequently occurring data. Also, Momento can gather log data, experience sampling, diary, and other qualitative data.

We present a general approach to temporal media segmentation using supervised classification. Given standard low-level features representing each time sample, we build intermediate features via pairwise similarity. The intermediate features comprehensively characterize local temporal structure, and are input to an efficient supervised classifier to identify shot boundaries. We integrate discriminative feature selection based on mutual information to enhance performance and reduce processing requirements. Experimental results using large-scale test sets provided by the TRECVID evaluations for abrupt and gradual shot boundary detection are presented, demonstrating excellent performance.

3D renderings can often look cold and impersonal or even cartoonish. They can also appear too crisply detailed . This can cause viewers to concentrate on specific details when they should be focusing on a more general idea or concept. With the techniques covered in this tutorial you will be able to turn your 3D renderings into "hand drawn" looking illustrations.

This chapter describes how the changing information about an individual's location, environment, and social situation can be used to initiate and facilitate people's interactions with one another, individually and in groups. Context-aware communication is contrasted with other forms of context-aware computing and we characterize applications in terms of design decisions along two dimensions: the extent of autonomy in context sensing and the extent of autonomy in communication action. A number of context-aware communication applications from the research literature are presented in five application categories. Finally, a number of issues related to the design of context-aware communication applications are presented.

This survey, aimed at information processing researchers, highlights intriguing but lesser known results, corrects misconceptions, and suggests research areas. Themes include: certainty in quantum algorithms; the "fewer worlds" theory of quantum mechanics; quantum learning; probability theory versus quantum mechanics.

In 2006 FXPAL submitted results for shot boundary detection, high-level feature extraction, and interactive search.

When people are checking in to flights, making reports to their company manager, composing music, delivering papers for exams in schools, or examining patients in hospitals, they all deal with documents and processes of documentation. In earlier times, documentation took place primarily in libraries and archives. While the latter are still important document institutions, documents today play a far more essential role in social life in many different domains and cultures. In this book, which celebrates the ten year anniversary of documentation studies in Tromsø, experts from many different disciplines, professional domains as well as cultures around the world present their way of dealing with documents, demonstrating many potential directions for the emerging broad field of documentation studies.

This chapter describes how the adaptive web technologies discussed in this book have been applied to news access. First, we provide an overview of different types of adaptivity in the context of news access and identify corre-sponding algorithms. For each adaptivity type, we briefly discuss representative systems that use the described techniques. Next, we discuss an in-depth case study of a personalized news system. As part of this study, we outline a user modeling approach specifically designed for news personalization, and present results from an evaluation that attempts to quantify the effect of adaptive news access from a user perspective. We conclude by discussing recent trends and novel systems in the adaptive news space.

This chapter discusses content-based recommendation systems, i.e., systems that recommend an item to a user based upon a description of the item and a profile of the user's interests. Content-based recommendation systems may be used in a variety of domains ranging from recommending web pages, news articles, restau-rants, television programs, and items for sale. Although the details of various systems differ, content-based recommendation systems share in common a means for describing the items that may be recommended, a means for creating a profile of the user that describes the types of items the user likes, and a means of comparing items to the user profile to determine what to recommend. The user profile is often created and updated automatically in response to feedback on the desirability of items that have been presented to the user.

With the techniques covered in this tutorial you will be able to produce two classic visual effects. First, I'll show you how to make animated titles by importing Photoshop files into Aftereffects. Next we'll add new scenic elements to some video footage, again using Photoshop. This technique will allow you to add or remove elements like tree or buildings from a shot. These techniques, especially the one we will use to alter the scene, are common to most visual effects. Watch the classic old 1933 version of King Kong. Willis O'Brien, the stop motion genius that animated Kong, pioneered the art of extending, or completely fabricating, scenery. Layering several elements painted on glass in front his puppets and rear projected footage allowed O'brien and RKO's visual effects artist Linwood Dunn to create King Kong's fantastic jungle scenes. It is said that these set-ups could be many feet deep.

Current search engines crawl the Web, download content, and digest this content locally. For multimedia content, this involves considerable volumes of data. Furthermore, this process covers only publicly available content because content providers are concerned that they otherwise loose control over the distribution of their intellectual property. We present the prototype of our secure and distributed search engine, which dynamically pushes content based feature extraction to image providers. Thereby, the volume of data that is transported over the network is significantly reduced, and the concerns mentioned above are alleviated. The distribution of feature extraction and matching algorithms is done by mobile software agents. Subsequent search requests performed upon the resulting feature indices by means of remote feature comparison can either be realized through mobile software agents, or by the use of implicitly created Web services which wrap the remote comparison functionality, and thereby improve the interoperability of the search engine. We give a description of the search engine's architecture and implementation, depict our concepts to integrate agent and Web service technology, and present quantitative evaluation results. Furthermore, we discuss related security mechanisms for content protection and server security.

Java is the predominant language for mobile agent systems, both for implementing mobile agent execution environments and for writing mobile agent applications. This is due to inherent support for code mobility by means of dynamic class loading and separable class name spaces, as well as a number of security properties, such as language safety and access control by means of stack introspection. However, serious questions must be raised whether Java is actually up to the task of providing a secure execution environment for mobile agents. At the time of writing, it has neither resource control nor proper application separation. In this article we take an in-depth look at Java as a foundation for secure mobile agent systems.

Load balancing has been an increasingly important issue for handling computational intensive tasks in a distributed system such as in Grid and cluster computing. In such systems, multiple server instances are installed for handling requests from client applications, and each request (or task) typically needs to stay in a queue before an available server is assigned to process it. In this paper, we propose a high-performance queueing method for implementing a shared queue for collaborative clusters of servers. Each cluster of servers maintains a local queue and queues of different clusters are networked to form a unified (or shared) queue that may dispatch tasks to all available servers. We propose a new randomized algorithm for forwarding requests in an overcrowded local queue to a networked queue based on load information of the local and neighboring clusters. The algorithm achieves both load balancing and locality awareness.

At their heart, most if not all information retrieval models utilize some form of term frequency. The notion is that the more often a query term occurs in a document, the more likely it is that document meets an information need. We examine an alternative. We propose a model which assesses the presence of a term in a document not by looking at the actual occurrence of that term, but by a set of nonindependent supporting terms, i.e. context. This yields a weighting for terms in documents which is different from and complementary to tf-based methods, and is beneficial for retrieval.

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.

In this demonstration, we are going to illustrate how to use a mobile camera to redirect documents to various devices connected to the same network

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 paper presents a method for facilitating document redirection in a physical environment via a mobile camera. With this method, a user is able to move documents among electronic devices, post a paper document to a selected public display, or make a printout of a white board with simple point-and-capture operations. More specifically, the user can move a document from its source to a destination by capturing a source image and a destination image in a consecutive order. The system uses SIFT (Scale Invariant Feature Transform) features of captured images to identify the devices a user is pointing to, and issues corresponding commands associated with identified devices. Unlike RF/IR based remote controls, this method uses object visual features as an all time 'transmitter' for many tasks, and therefore is easy to deploy. We present experiments on identifying three public displays and a document scanner in a conference room for evaluation.

We describe our work-in-progress: a "wizard-free" conference room designed for ease of use, yet retaining next-generation functionality. Called USE (Usable Smart Environments), our system uses multi-display systems, immersive conferencing, and secure authentication. It is based in cross-cultural ethnographic studies on the way people use conference rooms. The USE project has developed a flexible, extensible architecture specifically designed to enhance ease of use in smart environment technologies. The architecture allows customization and personalization of smart environments for particular people and groups, types of work, and specific physical spaces. The system consists of a database of devices with attributes, rooms and meetings that implements a prototype-instance inheritance mechanism through which contextual information (e.g. IP addresses application settings, phone numbers for teleconferencing systems, etc.) can be associated

In the UbiComp 2005 workshop "Ubiquitous computing in next generation conference rooms" we learned that usability is one of the primary challenges in these spaces. Nearly all "smart" rooms, though they often have interesting and effective functionality, are very difficult to simply walk in and use. Most such rooms have resident experts who keep the room's systems functioning, and who often must be available on an everyday basis to enable the meeting technologies. The systems in these rooms are designed for and assume the presence of these human "wizards"; they are seldom designed with usability in mind. In addition, people don't know what to expect in these rooms; as yet there is no technology standard for next-generation conference rooms. The challenge here is to strike an effective balance between usability and new kinds of functionality (such as multiple displays, new interfaces, rich media systems, new uploading/access/security systems, robust mobile integration, to name just a few of the functions we saw in last year's workshop). So, this year, we propose a workshop to focus more specifically on how the design of next-generation conference rooms can support usability: the tasks facing the real people who use these rooms daily. Usability in ubiquitous computing has been the topic of several papers and workshops. Focusing on usability in next-generation conference rooms lets us bring to bear some of the insights from this prior work in a delineated application space. In addition the workshop will be informed by the most recent usability research in ubiquitous computing, rich media, context-aware mobile systems, multiple display environments, and interactive physical environments. We also are vitally concerned with how usability in smart environments tracks (or doesn't) across cultures. Conference room research has been and remains a focal point for some of the most interesting and applied work in ubiquitous computing. It is also an area where there are many real-world applications and daily opportunities for user feed-back: in short, a rich area for exploring usable ubiquitous computing. We see a rich opportunity to draw together researchers not only from conference room research but also from areas such as interactive furniture/smart environments, rich media, social computing, remote conferencing, and mobile devices for a lively exchange of ideas on usability in applied ubicomp systems for conference rooms.

This paper describes a framework for detecting unusual events in surveillance videos. Most surveillance systems consist of multiple video streams, but traditional event detection systems treat individual video streams independently or combine them in the feature extraction level through geometric reconstruction. Our framework combines multiple video streams in the inference level, with a coupled hidden Markov Model (CHMM). We use two-stage training to bootstrap a set of usual events, and train a CHMM over the set. By thresholding the likelihood of a test segment being generated by the model, we build a unusual event detector. We evaluate the performance of our detector through qualitative and quantitative experiments on two sets of real world videos.

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.