Informedia Digital Video Library

The standard method for making the full content of audio and video material searchable is to annotate it with human-generated meta-data that describes the content in a way that the search can understand, as is done in the creation of multimedia CD-ROMs. However, for the huge amounts of data that could usefully be included in digital video and audio libraries, the cost of producing this meta-data is prohibitive. In the Informedia Digital Video Library, the production of the meta-data supporting the library interface is automated using techniques derived from artificial intelligence (AI) research. By applying speech recognition together with natural language processing, information retrieval, and image analysis, an interface has been produced that helps users locate the information they want, and navigate or browse the digital video library more effectively. Specific interface components include automatic titles, filmstrips, video skims, word location marking, and representative frames for shots. Both the user interface and the information retrieval engine within Informedia are designed for use with automatically derived meta-data, much of which depends on speech recognition for its production. Some experimental information retrieval results will be given, supporting a basic premise of the Informedia project: That speech recognition generated transcripts can make multimedia material searchable. The Informedia project emphasizes the integration of speech recognition, image processing, natural language processing, and information retrieval to compensate for deficiencies in these individual technologies. © 1998 John Wiley & Sons, Inc.

Video is a challenging material for digital libraries because it contains large amounts of data which must be processed quickly and because video programming has not been as conveniently structured for algorithmic processing as text. Since moving images are used as scholarly material in a number of disciplines, digital libraries must be able to support cataloging, browsing, and navigating through video collections. We have shown that computationally tractable algorithms can be used to solve some of the important problems in digital video libraries. While much further work needs to be done, we believe that signal and image processing algorithms will help us solve other important problems in video libraries.

Purpose– The purpose of this paper is to report on a user-centred analysis of video digital libraries and to present users’ criteria based on concepts emerging directly from the responses of study participants. As a time-based and multi-channeled format, video warrants considerations for information delivery through interactive tools such as digital libraries.Design/methodology/approach– A survey method was used to collect open-ended responses from participants. Content analysis was performed on the responses, and categories then emerged to form the coding scheme where simple and weighted frequencies were calculated to obtain a ranked set of users’ criteria. Cohen’sκwas 0.87, indicative of high-level of inter-coder reliability. In the end, 81 participants contributed a total of 385 open-ended responses, which were all then analysed and coded.Findings– The emergent coding method and continuous refinements to the coding scheme ultimately produced 28 criteria (subcategories) under four primary categories. Criteria corresponding to “retrieval functionality” of video digital libraries emerged as the highest, or most frequently referenced, primary category, while the “user interface”, “collection qualities”, and “user support” followed, respectively.Research limitations/implications– The primary research contribution is a baseline for video digital libraries that can be applicable throughout design and evaluation. Future studies can utilise findings presented here as guidance for the initial design stages and/or for assessing systems via targeted evaluations.Originality/value– While users’ criteria of digital libraries have been analysed from non-visual contexts, they have not been directly assessed as they pertain to users’ experiences and perceptions with video, which is needed as the nature and structure of video can influence users and use.

The number of channels of digital television is increasing, particularly the number that are free-to-air. However due to the nature of broadcasting, this morass of information is not, for the main part, organized---it is principally a succession of images and sound transmitted as multiplexed streams of data. Compare this deluge that terrestrially bombards our homes with the information available in the digital libraries we access over the Internet---stored using software purpose built to help organize carefully curated sets of documents. This project brings together these two seemingly incompatible concepts to develop a software environment that concurrently captures all the available live television channels---so a user does not need to proactively choose what to record---and segments them into files which are then imported into a digital video library with a user interface designed to work from a multimedia remote control. A shifting time-based window of all recordings is maintained---we settled on from the last two weeks so as to be practicably operable on a regular desktop PC. The system leverages off the information contained in the electronic program guide and the video recordings to generate metadata suitable for the digital library. A user evaluation of the developed prototype showed a high level of participant satisfaction across a range of attributes, notably date-based searching.

Technology usage is changing rapidly and is becoming a more mobile, more social and more multimedia-based experience. This is especially true in the area of content creation where mobile social applications used by crowds of people are challenging traditional ways of creating and distributing content, especially for applications like news dissemination. Libraries have traditionally functioned as repositories where the information content of a society is analysed, curated, organised and stored, acting as a permanent record of what is to be remembered from a society. How can this function be achieved by present-day libraries attempting to cope with mobile, social, multimedia content who's nature and utility of which change the type of information we wish to curate and store? This information is both dynamic and organic, posing challenges to the more fixed models of information in digital libraries. In this article we describe two digital library systems that archive video content from the sports domain, and which support user annotations and merging of diverse information sources in an integrated way. We report on analysis of the deployment of these two systems and highlight how they extend the traditional role of a (digital) library.

The color appearance of digital video imagery acquired from analog sources is affected by intrinsic device imperfections. Although the human visual system (HVS) is capable of perceiving color variations when comparing different acquisitions of the same video, it is able to identify the colors in an isolated image as well. Color based computer vision processes applied within digital video libraries do not have this capability and their performance is severely reduced. This paper presents a method for modeling the intrinsic color appearance given by acquisition devices. It is based on the approximation of the distribution of colors generated by a device using a mixture of Gaussians in RGB space. Its parameters are encoded in a specifically designed pattern, which provides a dense estimation of the distribution of colors along the whole RGB space. In this way, the model can be attached to every acquired video in order to put its original color appearance on record. The approximation by mixtures of Gaussians lets us define transformations between them that preserve the identity of colors. This fact is shown in the case of skin color segmentation, where the underlying concept of color is captured from samples obtained by a particular device. Other applications of color correction in digital video are pointed out in this paper as well.

Many commercial and academic disciplines need digital video libraries. Such libraries must provide the user with the opportunity to manipulate the material non-linearly. This paper discusses digital video libraries and various non-linear services these libraries will provide. The architectural components of such libraries are discussed and a model of user access is developed. Results from caching experiments utilizing that model are reported for several usage patterns and four cache organizations.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This paper proposes an abstraction mechanism of the low-level digital video features for the automatic retrievals of the explosion scenes from the digital video library. In the proposed abstraction mechanism, the regional dominant colors of the key frame and the motion energy of the shot are defined as the primary low-level visual features of the shot for the explosion scene retrievals. The regional dominant colors of shot are selected by dividing its key frame image into several regions and extracting their regional dominant colors, and the motion energy of the shot is defined as the edge image differences between key frame and its neighboring frame. Upon the extensive experimental results, we could argue that the recall and precision of the proposed abstraction and detecting algorithm are about 0.8, and also found that they are not sensitive to the thresholds.KeywordsColor HistogramEdge ImageRetrieval AlgorithmEdge PixelDominant ColorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Periodic broadcast and scheduled multicast have been shown to be very effective in reducing the demand on server bandwidth. While periodic broadcast is better for popular videos, scheduled multicast is more suitable for less popular ones. Work has also been done to show that a hybrid of these techniques offer the best performance. Existing hybrid schemes, however, assume that the characteristic of the workload does not change with time. This assumption is not true for many applications, such as movie on demand, digital video libraries, or electronic commerce. In this paper, we show that existing scheduled multicast techniques are not suited for hybrid designs. To address this issue, we propose a new approach and use it to design an adaptive hybrid strategy. Our technique adjusts itself to cope with a changing workload. We provide simulation results to demonstrate that the proposed technique is significantly better than the best static approach in terms of service latency, throughput, defection rate, and unfairness.

The automatic extraction and recognition of news captions and annotations can be of great help locating topics of interest in digital news video libraries. To achieve this goal, we present a technique, called Video OCR (Optical Character Reader), which detects, extracts, and reads text areas in digital video data. In this paper, we address problems, describe the method by which Video OCR operates, and suggest applications for its use in digital news archives. To solve two problems of character recognition for videos, low-resolution characters and extremely complex backgrounds, we apply an interpolation filter, multiframe integration and character extraction filters. Character segmentation is performed by a recognition-based segmentation method, and intermediate character recognition results are used to improve the segmentation. We also include a method for locating text areas using text-like properties and the use of a language-based postprocessing technique to increase word recognition rates. The overall recognition results are satisfactory for use in news indexing. Performing Video OCR on news video and combining its results with other video understanding techniques will improve the overall understanding of the news video content.

No abstract available.

This paper presents a user-centred video retrieval, or video digital library, study that examines different types of feedback. Separate user interface features, including one that collects and one that presents feedback, shape the evaluation of this study. Research questions were posed to examine both types of feedback and to measure the influence of certain factors on each. The experimental factors examined here, in association with feedback, included user actions, topic characteristics, search duration, levels of user satisfaction and domain familiarity. Laboratory-style search experiments employing 28 users from the field of science education were conducted, which asked the users to attempt six pre-designed search topics. Actions of the users and topic durations were recorded, and users were given a post-search questionnaire about the topics and their experiences and impressions of the experimental system. Results showed that users regularly requested feedback about a clip, beyond a keyframe, while searching, not browsing, and that requests varied significantly across certain topic categories. Findings also indicated that users’ requests for feedback were more general interactions and not associated with a search topic’s representation of the domain. On the other hand, users rarely contributed feedback about the relative importance of visual vs semantic qualities of search results in order to reformulate queries, regardless of any other experimental factor.

Live logging and posterity logging are the two basic applications for video databases. The former aims at providing effective annotation of video in quasi-real time and supports extraction of meaningful clips from the live stream; the latter provides annotation for later reuse of video material and is the prerequisite for retrieval by content from video digital libraries. Both require that information is adequately structured with interchange format and that annotation is performed, to a great extent, automatically. The video information structure must encompass both low-intermediate level video organization and event relationships that define specific highlights and situations. Analysis of the visual data of the video stream permits hints to be extracted, events identified and highlights detected. All of this must be supported by a-priori knowledge of the subject and effective reasoning engines capable of capturing the inherent semantics of the visual events.

BackgroundClinical reasoning is an essential medical competence that should be taught and assessed from the beginning of medical studies. These skills can be evaluated using the Script Concordance Test (SCT), which presents daily clinical scenarios characterised by uncertainty. Due to the lack of validated research on this method in Germany, particularly in the field of neurology, we developed and implemented an SCT at Ruhr University Bochum. We compared different teaching methods (clinical seminar vs. digital video course) and their outcomes on the examination.MethodsA group of 6th-year medical students who had received the same education completed an SCT after participating in either a clinical seminar or a digital video course. The SCT was developed using blueprints on stroke and epilepsy. The test consisted of 40 case vignettes with a total of 120 items. Initially, experts completed the test to establish the reference panel. The final high-stakes examination was created using the aggregate scoring method and an item analysis.ResultsThe SCT was completed by 15 experts and 59 students. The final SCT consisted of 112 items and achieved a Cronbach’s alpha of 0.85. A significant difference (p < 0.05) was observed between the experts, who achieved a mean score of 81.75, and the students on the first assessment day, who achieved a mean score of 68.92. No significant differences were found between the groups (interactive video course and seminar) or assessment time points. The questionnaire revealed a sense of insecurity in clinical decision-making before the SCT and highlighted the need to incorporate clinical reasoning practices from the beginning of medical studies to mitigate fear in uncertain situations. The SCT helped students structure decision-making processes and and improved their confidence in making decisions.ConclusionThe SCT is a reliable and valid tool for assessing medical students throughout their university education. Regular exposure to the SCT format would facilitate familiarity with its structure. We propose utilising the SCT as a learning tool rather than solely for assessment purposes. For instance, it could be integrated into teaching methodologies as a think-aloud exercise or incorporated into progress tests.

The Information Age is fully upon us. A recent article noted that there are perhaps 50 million people using the Internet on a regular basis, and That “the current growth rate is about 15% per month (!) and this could well continue until almost all of those in the ‘developed world’ are connected” [FM94, p. 30]. In addition, the digital domain consists not only of text but increasingly of other media representations, from graphics images to audio to motion video. As the amount of information and number of users exponentially escalate, more attention focuses on the basic problems of information management: How do you digitize information? How can you then visualize it and find what you need? How do you use and manipulate it effectively? How is it stored and managed? The proliferation of technical articles and special issues addressing these questions underscore their importance; see for example the special issue on Content-based retrieval [Nar95] or digital libraries [F+95]. This chapter will survey some of that work, especially that which relates to the treatment of video and the use of digital video libraries For education.