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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Lee, K. (2005). Semantic feature extraction based on video abstraction and temporal modeling. In Lecture Notes in Computer Science (Vol. 3522, pp. 392–400). Springer Verlag. https://doi.org/10.1007/11492429_48
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