A novel automatic shot boundary detection algorithm: robust to illumination and motion effect

Many researches have been done on shot boundary detection, but the performance of shot boundary detection approaches is yet to be addressed for the videos having sudden illumination and object/camera motion effects efficiently. In this paper, a novel dual-stage approach for an abrupt transition detection is proposed which is able to withstand under certain illumination and motion effects. Firstly, an adaptive Wiener filter is applied to the lightness component of the frame to retain some important information on both frequencies and LBP-HF is extracted to reduce the illumination effect. From the experimentation, it is also confirmed that the motion effect is also reduced in the first stage. Secondly, Canny edge difference is used to further remove the illumination and motion effects which are not handled in the first stage. TRECVid 2001 and TRECVid 2007 datasets are applied to analyze and validate our proposed algorithm. Experimental results manifest that the proposed system outperforms the state-of-the-art shot boundary detection techniques.

Task Dataset Model Metric Name Metric Value Global Rank Benchmark
Camera shot boundary detection MSU Shot Boundary Detection Benchmark NITS-CV-Lab-v1.0 F score 0.8470 # 1
FPS 24 # 10
Camera shot boundary detection TRECVID LBP-HF SBD F-measure (Recall) 0.94 # 1


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