Issue No. 03 - July-Sept. (2013 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MMUL.2012.62
Yonghong Tian , Peking University
Tiejun Huang , Peking University
Menglin Jiang , Peking University
Wen Gao , Peking University
For video copy detection, no single audio-visual feature, or single detector based on several features, can work well for all transformations. This article proposes a novel video copy-detection and localization approach with scalable cascading of complementary detectors and multiscale sequence matching. In this cascade framework, a soft-threshold learning algorithm is utilized to estimate the optimal decision thresholds for detectors, and a multiscale sequence matching method is employed to precisely locate copies using a 2D Hough transform and multigranularities similarity evaluation. Excellent performance on the TRECVID-CBCD 2011 benchmark dataset shows the effectiveness and efficiency of the proposed approach.
VIdeo coding, Videos, Threshold analysis, Learning systems, Sequential analysis, Multimedia communication, multiscale sequence matching, TRECVID-CBCD, multimedia, video copy detection, scalable cascading, complementary detectors, soft threshold learning
W. Gao, M. Jiang, T. Huang and Y. Tian, "Video Copy-Detection and Localization with a Scalable Cascading Framework," in IEEE MultiMedia, vol. 20, no. , pp. 72-86, 2013.