2005 | OriginalPaper | Buchkapitel
Semantic Feature Extraction Based on Video Abstraction and Temporal Modeling
verfasst von : Kisung Lee
Erschienen in: Pattern Recognition and Image Analysis
Verlag: Springer Berlin Heidelberg
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This paper presents a novel scheme of object-based video indexing and retrieval based on video abstraction and semantic event modeling. The proposed algorithm consists of three major steps; Video Object (VO) extraction, object-based video abstraction and statistical modeling of semantic features. Semantic feature modeling scheme is based on temporal variation of low-level features in object area between adjacent frames of video sequence. Each semantic feature is represented by a Hidden Markov Model (HMM) which characterizes the temporal nature of VO with various combinations of object features. The experimental results demonstrate the effective performance of the proposed approach.