Forecasting human actions and motion trajectories address the problem of predicting what a person is going to do next and how they will perform it. This is crucial in a wide range of applications, such as assisted living and future co-robotic settings. We propose to simultaneously learn actions and action-related human motion dynamics while existing works perform them independently. This paper presents a method to jointly forecast categories of human action and skeletal joint pose, allowing the two tasks to reinforce each other. As a result, our system can predict future actions and the motion trajectories that will result. To achieve this, we define a task of joint action classification and pose regression. We employ a sequence to sequence encoder-decoder model combined with multi-task learning to forecast future actions and poses progressively before the action happens. Experimental results on two public datasets, IkeaDB and OAD, demonstrate the effectiveness of the proposed method.

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 verified 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.

In this paper, we develop a system for the low-cost indoor localization and tracking problem using radio signal strength indicator, Inertial Measurement Unit (IMU), and magnetometer sensors. We develop a novel and simplified probabilistic IMU motion model as the proposal distribution of the sequential Monte-Carlo technique to track the robot trajectory. Our algorithm can globally localize and track a robot with a priori unknown location, given an informative prior map of the Bluetooth Low Energy (BLE) beacons. Also, we formulate the problem as an optimization problem that serves as the Backend of the algorithm mentioned above (Front-end). Thus, by simultaneously solving for the robot trajectory and the map of BLE beacons, we recover a continuous and smooth trajectory of the robot, corrected locations of the BLE beacons, and the time-varying IMU bias. The evaluations achieved using hardware show that through the proposed closed-loop system the localization performance can be improved; furthermore, the system becomes robust to the error in the map of beacons by feeding back the optimized map to the Front-end.

Accurate localization is a fundamental requirement for a variety of applications, ranging from industrial robot operations to location-powered applications on mobile devices. A key technical challenge in achieving this goal is providing a clean and reliable estimation of location from a variety of low-cost, uncalibrated sesnors. Many current techniques rely on Particle Filter (PF) based algorithms. They have proven successful at effectively fusing various sensors inputs to create meaningful location predictions. In this paper we build upon this large corpous of work. Like prior work, our technique fuses Received Signal Strength Indicator (RSSI) measurements from Bluetooth Low Energy (BLE) beacons with map information. A key contribution of our work is a new sensor model for BLE beacons that does not require the mapping from RSSI to distance. We further contribute a novel method of utilizing map information during the initialization of the system and during the resampling phase when new particles are generated. Using our proposed sensor model and map prior information the performance of the overall localization is improved by 1.20 m on comparing the 75thpercentile of the cumulative distribution with traditional localization techniques.

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 for meetings with asynchronous attendance. Such hypermeetings consist of a chain of video-recorded meetings with hyperlinks for navigating through them. Our HyperMeeting system supports the viewing of prior meetings during a videoconference. Natural viewing behavior such as pausing video generates hyperlinks between previous and current meetings. 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 topic and speaker segmentation. A user study showed that participants found hyperlinks useful but did not always understand where the links would take them. Experiences from longer-term use and the study results provide a good basis for future system improvements.

Distributed teams must co-ordinate a variety of tasks. To do so they need to be able to create, share, and annotate documents as well as discuss plans and goals. Many workflow tools support document sharing, while other tools support videoconferencing. However, there exists little support for connecting the two. In this work, we describe a system that allows users to share and markup content during web meetings. This shared content can provide important conversational props within the context of a meeting; it can also help users review archived meetings. Users can also extract content from meetings directly into their personal notes or other workflow tools.

Modern office work practices increasingly breach traditional boundaries of time and place, increasing breakdowns workers encounter when coordinating interactions with colleagues. We conducted interviews with 12 workers and identified key problems introduced by these practices. To address these problems we developed myUnity, a fully functional platform enabling rich workplace awareness and coordination. myUnity is one of the first integrated platforms to span mobile and desktop environments, both in terms of access and sensing. It uses multiple sources to report user location, availability, tasks, and communication channels. A pilot field study of myUnity demonstrated the significant value of pervasive access to workplace awareness and communication facilities, as well as positive behavioral change in day-to-day communication practices for most users. We present resulting insights about the utility of awareness technology in flexible work environments.

Although people are capturing more video with their mobile phones, digital cameras, and other devices, they rarely watch all that video. More commonly, users extract a still image from the video to print or a short clip to share with others. We created a novel interface for browsing through a video keyframe hierarchy to find frames or clips. The interface is shown to be more efficient than scrolling linearly through all keyframes. We developed algorithms for selecting quality keyframes and for clustering keyframes hierarchically. At each level of the hierarchy, a single representative keyframe from each cluster is shown. Users can drill down into the most promising cluster and view representative keyframes for the sub-clusters. Our clustering algorithms optimize for short navigation paths to the desired keyframe. A single keyframe is located using a non-temporal clustering algorithm. A video clip is located using one of two temporal clustering algorithms. We evaluated the clustering algorithms using a simulated search task. User feedback provided us with valuable suggestions for improvements to our system.

We present a large-scale Embedded Media Marker (EMM) identification system which allows users to retrieve relevant dynamic media associated with a static paper document via camera-phones. The user supplies a query image by capturing an EMM-signified patch of a paper document through a camera phone. The system recognizes the query and in turn retrieves and plays the corresponding media on the phone. Accurate image matching is crucial for positive user experience in this application. To address the challenges posed by large datasets and variation in camera-phone-captured query images, we introduce a novel image matching scheme based on geometrically consistent correspondences. A hierarchical scheme, combined with two constraining methods, is designed to detect geometric constrained correspondences between images. A spatial neighborhood search approach is further proposed to address challenging cases of query images with a large translational shift. Experimental results on a 200k+ dataset show that our solution achieves high accuracy with low memory and time complexity and outperforms the baseline bag-of-words approach. © 2011 ACM.

Modern office work practices increasingly breach traditional boundaries of time and place, making it difficult to interact with colleagues. To address these problems, we developed myUnity, a software and sensor platform that enables rich workplace awareness and coordination. myUnity is an integrated platform that collects information from a set of independent sensors and external data aggregators to report user location, availability, tasks, and communication channels. myUnity's sensing architecture is component-based, allowing channels of awareness information to be added, updated, or removed at any time. Our current system includes a variety of sensor and data input, including camera-based activity classification, wireless location trilateration, and network activity monitoring. These and other input channels are combined and composited into a single, highlevel presence state. Early studies of a myUnity deployment have demonstrated that use of the platform allows quick access to core awareness information and show its utility in supporting communication and collaboration in the modern workplace.

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.

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.

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.

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.

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.

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 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 similar 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 concentrate 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 selected for the dragged objects.

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 at a later time. Different views within the user interface provide spatial information for easier navigation. Our system, with over twenty video cameras installed in hallways and other public spaces in our office building, has been in constant use for almost a year.

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 fatade; 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.

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 and 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, interphoto 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.

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.

This work 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.

We present similarity-based methods to cluster digital photos by time and image content. This approach is general, unsupervised, and makes minimal assumptions regarding the structure or statistics of the photo collection. We describe versions of the algorithm using temporal similarity with and without content-based similarity, and compare the algorithms with existing techniques, measured against ground-truth clusters created by humans.

A novel method is presented for inaudibly hiding information in an audio signal by subtly applying time-scale modification to segments of the signal. The sequence, duration, and degree of the time-scale modifications are the parameters which encode information in the altered signal. By comparing the altered signal with a reference copy, compressed and expanded regions can be identified and the hidden data recovered. This approach is novel and has several advantages over other methods: it is theoretically noiseless, it introduces no spectral distortion, and it is robust to all known methods of reproduction, compression, and transmission.

We created an improved layout algorithm for automatically generating visual video summaries reminiscent of comic book pages. The summaries are comprised of images from the video that are sized according to their importance. The algorithm performs a global optimization with respect to a layout cost function that encompasses features such as the number of resized images and the amount of whitespace in the presentation. The algorithm creates summaries that: always fit exactly into the requested area, are varied by containing few rows with images of the same size, and have little whitespace at the end of the last row. The layout algorithm is fast enough to allow the interactive resizing of the summaries and the subsequent generation of a new layout.

We created an alternative approach to existing video summaries that gives viewers control over the summaries by selecting hyper-links 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.

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 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 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-on-demand 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.

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.

Technology can play an important role in enabling people to interact with each other. The Web is one such technology with the affordances for sharing information and for connecting people to people. In this paper, we describe the design of two social interaction Web sites for two different social groups. We review several related efforts to provide principles for creating social interaction environments and describe the specific principles that guided our design. To examine the effectiveness of the two sites, we analyze the usage data. Finally, we discuss approaches for encouraging participation and lessons learned.

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

We present methods for automatic and semi-automatic creation of music videos, given an arbitrary audio soundtrack and source video. Significant audio changes are automatically detected; similarly, the source video is automatically segmented and analyzed for suitability based on camera motion and exposure. Video with excessive camera motion or poor contrast is penalized with a high unsuitability score, and is more likely to be discarded in the final edit. High quality video clips are then automatically selected and aligned in time with significant audio changes. Video clips are adjusted to match the audio segments by selecting the most suitable region of the desired length. Besides a fully automated solution, our system can also start with clips manually selected and ordered using a graphical interface. The video is then created by truncating the selected clips (preserving the high quality portions) to produce a video digest that is synchronized with the soundtrack music, thus enhancing the impact of both.

Article Share on LiteMinutes: an Internet-based system for multimedia meeting minutes Authors: Patrick Chiu FX Palo Alto Laboratory, 3400 Hillview Avenue, Bldg. 4, Palo Alto, CA FX Palo Alto Laboratory, 3400 Hillview Avenue, Bldg. 4, Palo Alto, CAView Profile , John Boreczky FX Palo Alto Laboratory, 3400 Hillview Avenue, Bldg. 4, Palo Alto, CA FX Palo Alto Laboratory, 3400 Hillview Avenue, Bldg. 4, Palo Alto, CAView Profile , Andreas Girgensohn FX Palo Alto Laboratory, 3400 Hillview Avenue, Bldg. 4, Palo Alto, CA FX Palo Alto Laboratory, 3400 Hillview Avenue, Bldg. 4, Palo Alto, CAView Profile , Don Kimber FX Palo Alto Laboratory, 3400 Hillview Avenue, Bldg. 4, Palo Alto, CA FX Palo Alto Laboratory, 3400 Hillview Avenue, Bldg. 4, Palo Alto, CAView Profile Authors Info & Claims WWW '01: Proceedings of the 10th international conference on World Wide WebMay 2001 Pages 140–149https://doi.org/10.1145/371920.371971Online:01 April 2001Publication History 40citation1,043DownloadsMetricsTotal Citations40Total Downloads1,043Last 12 Months45Last 6 weeks6 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

This paper presents a method for generating compact pictorial summarizations of video. We developed a novel approach for selecting still images from a video suitable for summarizing the video and for providing entry points into it. Images are laid out in a compact, visually pleasing display reminiscent of a comic book or Japanese manga. Users can explore the video by interacting with the presented summary. Links from each keyframe start video playback and/or present additional detail. Captions can be added to presentation frames to include commentary or descriptions such as the minutes of a recorded meeting. We conducted a study to compare variants of our summarization technique. The study participants judged the manga summary to be significantly better than the other two conditions with respect to their suitability for summaries and navigation, and their visual appeal.

No abstract available.

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.

This paper describes techniques for classifying video frames using statistical models of reduced DCT or Hadamard transform coefficients. When decimated in time and reduced using truncation or principal component analysis, transform coefficients taken across an entire frame image allow rapid modeling, segmentation and similarity calculation. Unlike color-histogram metrics, this approach models image composition and works on grayscale images. Modeling the statistics of the transformed video frame images gives a likelihood measure that allows video to be segmented, classified, and ranked by similarity for retrieval. Experiments are presented that show an 87% correct classification rate for different classes. Applications are presented including a content-aware video browser.

This paper presents methods for automatically creating pictorial video summaries that resemble comic books. The relative importance of video segments is computed from their length and novelty. Image and audio analysis is used to automatically detect and emphasize meaningful events. Based on this importance measure, we choose relevant keyframes. Selected keyframes are sized by importance, and then efficiently packed into a pictorial summary. We present a quantitative measure of how well a summary captures the salient events in a video, and show how it can be used to improve our summaries. The result is a compact and visually pleasing summary that captures semantically important events, and is suitable for printing or Web access. Such a summary can be further enhanced by including text captions derived from OCR or other methods. We describe how the automatically generated summaries are used to simplify access to a large collection of videos.

No abstract available.

The Digestor system automatically converts web-based documents designed for desktop viewing into formats appropriate for handheld devices with small display screens, such as Palm-PCs, PDAs, and cellular phones. Digestor employs a heuristic planning algorithm and a set of structural page transformations to produce the ‘best’ looking document for a given display size. Digestor can also be instructed, via a scripting language, to render portions of documents, thereby avoiding navigation through many screens of information. Two versions of Digestor have been deployed, one that re-authors HTML into HTML for conventional browsers and one that converts HTML into HDML for Phone.com's micro-browsers. Digestor provides a crucial technology for rapidly accessing, scanning and processing information from arbitrary web-based documents from any location reachable by wired or unwired communication.

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. 1.1 Keywords Content-based retrieval, video, speaker identification, automatic analysis, visualization, skimming 2.

No abstract available.

The prevalence of audio and video options on computers, coupled with the promise of bandwidth, have many prognosticators predicting a revolution in human communications.But what if the revolution materializes and no users show up?We were confronted with this question when we began deploying and studying the use of a video-based, background awareness application within our organization.Repeatedly, new users raised strong concerns about self-presentation, surveillance, privacy, video snapshots, and lack of audience cues.We describe how we addressed these concerns by evolving the application.As a consequence, we are also redesigning the user interface to the application.

Goals and content: The tutorial discusses how to develop collaborative applications using the WWW Shell as a rapid prototyping and development platform. Using an example collaborative application, we introduce particular development topics to illustrate the suitability of the WWW shell and its use. Also, we discuss recent additions in functionality as well as constraints with the WWW Shell approach.

An approach that embeds human-computer cooperative problem-solving tools into knowledge-based design environments that work in conjunction with human software designers in specific application domains is described. This human-centered approach takes advantage of peoples' ability to understand and incrementally reformulate their problems, while allowing them to contribute to the gradual improvement of the underlying knowledge base. The notion of evolution circumvents the inability of the original builders of a design environment to anticipate all future needs and knowledge for complete coverage of a domain. The access and development of knowledge is supported in a cycle of location, comprehension, and modification. Modification includes the evolution of the knowledge base and tools. A framework for building such tools and mechanisms is described and illustrated in terms of three systems: CATALOGEXPLORER, EXPLAINER, and MODIFIER. User studies of these systems demonstrate the promise and the limitations of the design environment approach.>

No abstract available.

Convivial systems encourage users to be actively engaged in generating creative extensions to the artifacts given to them. Convivial systems have the potential to break down the counterproductive barrier between programming and using programs.