Abstract
Video partitioning is a key issue in video classification that facilitates the management of video resources. The video partitioning involves the detection of boundaries between uninterrupted segments (video shots). Shot boundaries can be classified into two categories, gradual transition and abrupt change. Detection of a gradual transition is considered to be difficult. Few methods have been reported for gradual transition detection. In this paper, a new approach called Two Measures Two Thresholds (TMTT) is proposed. The method requires the use of two measures and consequently two thresholds. By comparing the gray level histogram difference of consecutive frames with a smaller Threshold ( Ts ), possible shot boundaries are located. Then false boundaries are discarded by comparing their color ratio histogram with another threshold that is used to measure the similarity of content of the frames. The efficiency of TMTT is promising according to the analysis of some experimental results.
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Li, D., Lu, H., Zhang, D. (2000). Video Segmentation by Two Measures and Two Thresholds. In: Leung, K.S., Chan, LW., Meng, H. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents. IDEAL 2000. Lecture Notes in Computer Science, vol 1983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44491-2_66
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DOI: https://doi.org/10.1007/3-540-44491-2_66
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