Abstract
Video copy detection techniques are used to detect copies of video widely, this paper proposed a new algorithm based on spatiotemporal analysis for copy detection and compares detection precision and efficiency with existing algorithms. The descriptor encodes the structure of video key frames by computing uniform Local Binary Pattern with rotation invariance. Besides, Chi-square tests are employed to speed up the matching process. The proposed algorithm can deal with various kinds of video transformations, such as brightness conversion, sharpen, contrast and gray scale, especially for video rotation which is not well addressed in existing algorithms. The results of experiments tested on TRECVID 2015 dataset, experimental results indicate that precision and recall are improved, proposed algorithm is with good robustness and discrimination accuracy, detection performance is improved further.
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