Video copy recognition by oriented PCA and statistical analysis
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Efficient advertisement discovery for audio podcast content using candidate segmentation
EURASIP Journal on Audio, Speech, and Music Processing
TV program segmentation using multi-modal information fusion
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Efficient mining of repetitions in large-scale TV streams with product quantization hashing
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
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This paper aims at repeat clip mining and knowledge discovery from video data. A unified approach is proposed to detect both unknown video repeats and known video clips of arbitrary length. Two detectors in a cascade structure are employed to achieve fast and accurate detection, and a reinforcement learning approach is adopted to efficiently maximize detection accuracy. In this approach very short video repeats (<1 s) and long ones can be detected by a single process, while overall accuracy remains high. Since video segmentation is essential for repeat detection, performance analysis is also conducted for several segmentation methods. Furthermore we propose a method to analyze video syntactical structure based on short video repeats detection. Experimental results on news videos demonstrate that identifying short video repeats is an effective way for video structure discovery and syntactical segmentation