AUTOMATED VIDEO SEGMENTATION USING COMPUTER VISION TECHNIQUES
Hun-Woo Yoo, Dong‐Sik Jang · International Journal of Information Technology & Decision Making · 2004
A video segmentation method is proposed in this paper. For abrupt cut detection, inter-frame similarities are computed using gray-level and edge histograms and a cut is declared when the similarities are under the predetermined threshold value. Gradual shot boundary detection is decided based on the similarities between the current frame and the previous shot boundary frame. Correlation coefficients are used to obtain universal threshold values, which are applied to various video data. Experimental results show that the proposed method provides 95% recall and 80% precision rates for abrupt cuts, and 83% recall and 54% precision rates for gradual changes.