social computing

This paper describes a new system for panoramic two-way video communication. Digitally combining images from an array of inexpensive video cameras results in a wide-field panoramic camera, from inexpensive off-the-shelf hardware. This system can aid distance learning in several ways, by both presenting a better view of the instructor and teaching materials to the students, and by enabling better audience feedback to the instructor. Because the camera is fixed with respect to the background, simple motion analysis can be used to track objects and people of interest. Electronically selecting a region of this results in a rapidly steerable "virtual camera." We present system details and a prototype distance-learning scenario using multiple panoramic cameras.

As more information is made available online, users collect information in personal information spaces like bookmarks and emails. While most users feel that organizing these collections is crucial to improve access, studies have shown that this activity is time consuming and highly cognitive. Automatic classification has been used but by relying on the full text of the documents, they do not generate personalized classifications. Our approach is to give users the ability to annotate their documents as they first access them. This annotation tool is unobtrusive and welcome by most users who generally miss this facility when dealing with digital documents. Our experiments show that these annotations can be used to generate personalized classifications of annotated Web pages.

While hypertext was originally conceived for the management of scientific and technical information, it has been embraced with great enthusiasm by several members of the literary community for the promises it offers towards new approaches to narrative. Experiments with hypertext-based interactive narrative were originally based solely on verbal text but have more recently extended to include digital video artifacts. The most accomplished of these experiments, HyperCafe, provided new insights into the nature of narrative and how it may be presented; but it also offered an opportunity to reconsider other text types. This paper is an investigation of the application of an approach similar to HyperCafe to a descriptive text. We discuss how the approach serves the needs of description and illustrate the discussion with a concrete example. We then conclude by considering the extent to which our experiences with description may be applied to our continuing interest in narrative.

Modern window-based user interface systems generate user interface events as natural products of their normal operation. Because such events can be automatically captured and because they indicate user behavior with respect to an application's user interface, they have long been regarded as a potentially fruitful source of information regarding application usage and usability. However, because user interface events are typically voluminos and rich in detail, automated support is generally required to extract information at a level of abstraction that is useful to investigators interested in analyzing application usage or evaluating usability. This survey examines computer-aided techniques used by HCI practitioners and researchers to extract usability-related information from user interface events. A framework is presented to help HCI practitioners and researchers categorize and compare the approaches that have been, or might fruitfully be, applied to this problem. Because many of the techniques in the research literature have not been evaluated in practice, this survey provides a conceptual evaluation to help identify some of the relative merits and drawbacks of the various classes of approaches. Ideas for future research in this area are also presented. This survey addresses the following questions: How might user interface events be used in evaluating usability? How are user interface events related to other forms of usability data? What are the key challenges faced by investigators wishing to exploit this data? What approaches have been brought to bear on this problem and how do they compare to one another? What are some of the important open research questions in this area?

While hypermedia is usually presented as a way to offer content in a nonlinear manner, hypermedia structure tends to reinforce the assumption that reading is basically a linear process. Link structures provide a means by which the reader may choose different paths to traverse; but each of these paths is fundamentally linear, revealed through either a block of text or a well-defined chain of links. While there are experiences that get beyond such linear constraints, such as driving a car, it is very hard to capture this kind of non-linearity, characterized by multiple sources of stimuli competing for attention, in a hypermedia document. This paper presents a multi-channel document infrastructure that provides a means by which all such sources of attention are presented on a single "page" (i.e., a display with which the reader interacts) and move between background and foreground in response to the activities of the reader. The infrastructure thus controls the presentation of content with respect to four dimensions: visual, audio, interaction support, and rhythm.

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 introduce an audio retrieval-by-example system for orchestral music. Unlike many other approaches, this system is based on analysis of the audio waveform and does not rely on symbolic or MIDI representations. ARTHUR retrieves audio on the basis of long-term structure, specifically the variation of soft and louder passages. The long-term structure is determined from envelope of audio energy versus time in one or more frequency bands. Similarity between energy profiles is calculated using dynamic programming. Given an example audio document, other documents in a collection can be ranked by similarity of their energy profiles. Experiments are presented for a modest corpus that demonstrate excellent results in retrieving different performances of the same orchestral work, given an example performance or short excerpt as a query.

Richard Feynman's observation that quantum mechanical effects could not be simulated efficiently on a computer led to speculation that computation in general could be done more efficiently if it used quantum effects. This speculation appeared justified when Peter Shor described a polynomial time quantum algorithm for factoring integers. In quantum systems, the computational space increases exponentially with the size of the system which enables exponential parallelism. This parallelism could lead to exponentially faster quantum algorithms than possible classically. The catch is that accessing the results, which requires measurement, proves tricky and requires new non-traditional programming techniques. The aim of this paper is to guide computer scientists and other non-physicists through the conceptual and notational barriers that separate quantum computing from conventional computing. We introduce basic principles of quantum mechanics to explain where the power of quantum computers comes from and why it is difficult to harness. We describe quantum cryptography, teleportation, and dense coding. Various approaches to harnessing the power of quantum parallelism are explained, including Shor's algorithm, Grover's algorithm, and Hogg's algorithms. We conclude with a discussion of quantum error correction.

In accessing large collections of digitized videos, it is often difficult to find both the appropriate video file and the portion of the video that is of interest. This paper describes a novel technique for determining keyframes that are different from each other and provide a good representation of the whole video. We use keyframes to distinguish videos from each other, to summarize videos, and to provide access points into them. The technique can determine any number of keyframes by clustering the frames in a video and by selecting a representative frame from each cluster. Temporal constraints are used to filter out some clusters and to determine the representative frame for a cluster. Desirable visual features can be emphasized in the set of keyframes. An application for browsing a collection of videos makes use of the keyframes to support skimming and to provide visual summaries.

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 describe a way to make a hypermedia meeting record from multimedia meeting documents by automatically generating links through image matching. In particular, we look at video recordings and scanned paper handouts of presentation slides with ink annotations. The algorithm that we employ is the Discrete Cosine Transform (DCT). Interactions with multipath links and paper interfaces are discussed.

Much of hypertext narrative relies on links to shape a reader's interaction with the text. But links may be too limited to express ambiguity, imprecision, and entropy, or to admit new modes of participation short of full collaboration. We use an e-book form to explore the implications of freeform annotation-based interaction with hypertext narrative. Readers' marks on the text can be used to guide navigation, create a persistent record of a reading, or to recombine textual elements as a means of creating a new narrative. In this paper, we describe how such an experimental capability was created on top of XLibris, a next generation e-book, using Forward Anywhere as the hypernarrative. We work through a scenario of interaction, and discuss the issues the work raises

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.