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Konstanz, Univ., Diplomarb., 2002.

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Video streaming is becoming a major channel for distance learning (or e-learning). A tremendous number of videos for educational purpose are capturedand archived in various e-learning systems today throughout schools, corporations and over the Internet. However, making information searchable and browsable, and presenting results optimally for a wide range of users and systems, remains a challenge.In this work two core algorithms have been developedto support effective browsing and searching of educational videos. The first is a fully automatic approach that recognizes slides in the videowith high accuracy. Built upon SIFT (scale invariant feature transformation) keypoint matching using RANSAC (random sample consensus), the approach is independent of capture systems and can handle a variety of videos with different styles and plentiful ambiguities. In particular, we propose a multi-phase matching pipeline that incrementally identifies slides from the easy ones to the difficult ones. We achieve further robustness by using the matching confidence as part of a dynamic Hidden Markov model (HMM) that integrates temporal information, taking camera operations into account as well.The second algorithm locates slides in the video. We develop a non-linear optimization method (bundle adjustment) to accurately estimate the projective transformations (homographies) between slides and video frames. Different from estimating homography from a single image, our method solves a set of homographies jointly in a frame sequence that is related to a single slide.These two algorithms open up a series of possibilities for making the video content more searchable, browsable and understandable, thus greatly enriching the user's learning experience. Their usefulness has been demonstrated in the SLIC (Semantically Linking Instructional Content) system, which aims to turnsimple video content into fully interactive learning experience for students and scholars.

Probleme bei der Bereitstellung eines Browsing Dienstes via Samba in (fremdadministrierten) heterogenen Netzen. Lösungen und Konfigurationsmöglichkeiten werden behandelt.

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Rich-prospect browsers aid research tasks by providing a meaningful representation of every item in a collection and tools to manipulate the display (Ruecker 2003). A number of rich-prospect browsers have been developed for exploring collections of items that can be represented visually. Several disciplines have recently shown interest in interfaces that attempt to leverage metadata in order to offer superior browsing environments. This thesis examines the potential of applying rich-prospect browsing principles to the exploration of text collections by taking advantage of the metadata-rich text collections that are available through the World Wide Web. It also introduces and assesses the Texttiles browser, an implementation of rich-prospect browsing designed specifically for exploring text collections. Fourteen students participated in a qualitative usability study that evaluated the browser through two different testing approaches in a variety of research tasks: Human-Computer Pragmatics (Anvik 2007) and Affordance Strength Model (Ruecker 2006b). Participants found the Texttiles browser to be a useful tool to explore text collections, understood how rich prospect browsing principles help explore collection, and were satisfied with the browser’s implementation of those principles. Participants also suggested some improvements to the browsers. The results of this study uncovered two new ideas regarding the importance of order and direct manipulation of the data. This thesis reinforces the rich-prospect browsing principles of meaningful representation, display manipulation, and prospect, and provides directions for future research.

Thesis (doctoral)--Swedish University of Agricultural Sciences, 2007. / Thesis documentation sheet inserted. Includes appendix of four papers and manuscripts, three co-authored with others. Includes bibliographical references. Also issued electronically via World Wide Web in PDF format; online version lacks appendix.

Thesis (M.S.)--University of Delaware, 2007. / Principal faculty advisor: Jacob L. Bowman, Dept. of Entomology & Wildlife Ecology. Includes bibliographical references.