A fast shot matching strategy for detecting duplicate sequences in a television stream
Proceedings of the 2nd international workshop on Computer vision meets databases
Detecting repeats for video structuring
Multimedia Tools and Applications
Clip based video summarization and ranking
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
A Clustering Technique for Video Copy Detection
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Efficient content-based video retrieval by mining temporal patterns
Proceedings of the 9th International Workshop on Multimedia Data Mining: held in conjunction with the ACM SIGKDD 2008
Query by shots: retrieving meaningful events using multiple queries and rough set theory
Proceedings of the 9th International Workshop on Multimedia Data Mining: held in conjunction with the ACM SIGKDD 2008
Evaluation of video news classification techniques for automatic content personalisation
International Journal of Advanced Media and Communication
Video copy detection by fast sequence matching
Proceedings of the ACM International Conference on Image and Video Retrieval
Video news classification for automatic content personalization: a genetic algorithm based approach
Proceedings of the 14th Brazilian Symposium on Multimedia and the Web
Effective content-based video retrieval using pattern-indexing and matching techniques
Expert Systems with Applications: An International Journal
Video clip matching using MPEG-7 descriptors and edit distance
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
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In this paper, we propose a new algorithm to find video clips with different temporal durations and some spatial variations. We adopt a longest common sub-sequence (LCS) matching technique for measuring the temporal similarity between video clips. Based on the measure we propose 3 techniques to improve the retrieval effectiveness. First, we use a few coefficients in the low frequency region of DCT block as the basis to represent spatial features. Second, we heuristically determine a suitable quantization step-size for visual features to better tolerate spatial variations of similar video clips and propose a paired quantizer method. Third, we incorporate the compactness and/or continuity of matched common sub-sequences in the LCS measure to better reflect temporal characteristics of video. The performance of the proposed algorithm shows an improvement of 63.5% in terms of MAP (mean average precision) as compared to an existing algorithm. The results show that our approach is effective for news video retrieval.