Detecting topical events in digital video
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Automatically extracting highlights for TV Baseball programs
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Omni-face detection for video/image content description
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Classification of general audio data for content-based retrieval
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
A multimedia delivery architecture for IPTV with P2P-based time-shift support
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
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Current personal Vido recorders make it very easy for consumers to record whole TV programs. Our research however, focuses on personalizing TV at a sub-program level. We use a traditional Content-Based Information Retrieval system architecture consisting of archiving and retrieval modules. The archiving module employs a three-layered, multimodal integration framework to segment, analyze, characterize, and classify segments. The retrieval module relies on users personal preferences to deliver both full programs and video segments of interest. We tested retrieval concepts with real users and discovered that they see more value in segmenting non-narrative programs (e.g. news) than narrative programs (e.g. movies). We benchmarked individual algorithms and segment classification for celebrity and financial segments as instances of non-narrative content. For celebrity segments we obtained a total precision of 94.1% and recall of 85.7%, and for financial segments a total precision of 81.1% and a recall of 86.9%.