Similarity Search in High Dimensions via Hashing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Finding and identifying unknown commercials using repeated video sequence detection
Computer Vision and Image Understanding
Real-Time Commercial Recognition Using Color Moments and Hashing
CRV '07 Proceedings of the Fourth Canadian Conference on Computer and Robot Vision
UQLIPS: a real-time near-duplicate video clip detection system
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Audio-based automatic management of TV commercials
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Similarity searching techniques in content-based audio retrieval via hashing
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Robust color histogram descriptors for video segment retrieval and identification
IEEE Transactions on Image Processing
Pruned multi-level successive elimination algorithm for TV commercial recognition
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
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In this paper, a coarse-to-fine matching strategy and corresponding approaches are proposed to address the two key research issues in commercial recognition, which are robust signature generation and efficient indexing structure. Specially, aiming at resisting the visual perception distortion, some novel and robust video content signatures are extracted by exploiting the global and local photometric and spatial properties. Then, to introduce a coarse-to-fine indexing structure, Locality Sensitive Hash (LSH) is applied to accelerate the initial coarse retrieval procedure. And the Fine Granularity Successive Elimination (FGSE) is triggered to eliminate rapidly those irrelevant candidates which have passed the coarse matching process. In addition, a heuristic temporal consistency maintenance approach is presented for further decreasing false alarms after fine matching process in regard to the temporal correlation. The promising experimental results show the effectiveness of the proposed strategy with respect to large video data collections.