Video Clustering Using SuperHistograms in Large Archives
VISUAL '00 Proceedings of the 4th International Conference on Advances in Visual Information Systems
Motion Activity Based Shot Identification and Closed Caption Detection for Video Structuring
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Efficient matching and clustering of video shots
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
Content-based retrieval of video shot using the-improved nearest feature line method
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
IEEE Transactions on Circuits and Systems for Video Technology
Fast and robust object-extraction framework for object-based streaming system
International Journal of Virtual Technology and Multimedia
Robust video sequence retrieval using a novel object-based T2D-histogram descriptor
Journal of Visual Communication and Image Representation
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
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Semantic feature extraction of video shots and fast video sequence matching are important and required for efficient retrieval in a large video database. In this paper, a novel mechanism of similarity retrieval is proposed. Similarity measure between video sequences considering the spatio-temporal variation through consecutive frames is presented. For bridging the semantic gap between low-level features and the rich meaning that users desire to capture, video shots are analyzed and characterized by the high-level feature of motion activity in compressed domain. The extracted features of motion activity are further described by the 2D-histogram that is sensitive to the spatio-temporal variation of moving objects. In order to reduce the dimensions of feature vector space in sequence matching, Discrete Cosine Transform (DCT) is exploited to map semantic features of consecutive frames to the frequency domain while retains the discriminatory information and preserves the Euclidean distance between feature vectors. Experiments are performed on MPEG-7 testing videos, and the results of sequence matching show that a few DCT transformed coefficients are adequate and thus reveal the effectiveness of the proposed mechanism of video retrieval.