CONTENTUS—technologies for next generation multimedia libraries

Nandzik, Jan; Litz, Berenike; Flores-Herr, Nicolas; Löhden, Aenne; Konya, Iuliu; Baum, Doris; Bergholz, André; Schönfuβ, Dirk; Fey, Christian; Osterhoff, Johannes; Waitelonis, Jörg; Sack, Harald; Kohler, Ralf; Ndjiki-Nya, Patrick

doi:10.1007/s11042-011-0971-2

Cited by 16 publications

(2 citation statements)

References 36 publications

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“…that enables a more flexible search function. In the CONTENTUS [18] project, a contentbased semantic multimedia retrieval system has been developed. After the digitization of media data, several analysis techniques e.g., OCR, ASR, video segmentation, automated speaker recognition etc.…”

Section: Content-based Video Searchmentioning

confidence: 99%

Content Based Lecture Video Retrieval Using Speech and Video Text Information

Yang

Meinel

2014

IEEE Trans. Learning Technol.

146

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In the last decade e-lecturing has become more and more popular. The amount of lecture video data on the World Wide Web (WWW) is growing rapidly. Therefore, a more efficient method for video retrieval in WWW or within large lecture video archives is urgently needed. This paper presents an approach for automated video indexing and video search in large lecture video archives. First of all, we apply automatic video segmentation and key-frame detection to offer a visual guideline for the video content navigation. Subsequently, we extract textual metadata by applying video Optical Character Recognition (OCR) technology on key-frames and Automatic Speech Recognition (ASR) on lecture audio tracks. The OCR and ASR transcript as well as detected slide text line types are adopted for keyword extraction, by which both video-and segment-level keywords are extracted for content-based video browsing and search. The performance and the effectiveness of proposed indexing functionalities is proven by evaluation.Index Terms-Lecture videos, automatic video indexing, content-based video search, lecture video archives ! • The authors are at Hasso-Plattner-Institute for Software Systems Engineering GmbH (HPI), he received the doctorate degree at the Hasso-Plattner-Institute for IT-Systems Engineering (HPI) at the University of Potsdam. His current research interests revolve around multimedia analysis, information retrieval, semantic technology, content based video search technology. He is involved in the development of the Web-University project space enhancement of the tele-TASK video recording system.

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Section: Content-based Video Searchmentioning

confidence: 99%

Content Based Lecture Video Retrieval Using Speech and Video Text Information

Yang

Meinel

2014

IEEE Trans. Learning Technol.

146

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“…music). 12 The second part of the automated speech recognition (ASR) is a speech to text analysis 13 , where the auditive structure is matched to (the spoken) words. The quality of the results is, however, dependent upon the quality of the speaker; dialects, background noises and voice overlaps can be problematic.…”

Section: Use Case For the Av-portalmentioning

confidence: 99%

TIB's Portal for audiovisual media

Neumann

Plank

2014

IFLA Journal

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The German National Library of Science and Technology (TIB) is developing a web-based platform for audiovisual media. The forthcoming audiovisual portal optimizes access to scientific videos such as computer animations, lecture and conference recordings. TIB's AV- Portal offers new methods for searching within videos enabled by automated video analysis with scene, speech, text and image recognition. Search results are connected to new knowledge by linking the data semantically. This paper aims at describing the TIB's portal for audiovisual media and the multimedia retrieval technologies as well as the added value for libraries and their users.

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