A new key frame representation for video segment retrieval

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Abstract
In this paper, we propose an optimal key frame representation scheme based on global statistics for video shot retrieval. Each pixel in this optimal key frame is constructed by considering the probability of occurrence of those pixels at the corresponding pixel position among the frames in a video shot. Therefore, this constructed key frame is called temporally maximum occurrence frame (TMOF), which is an optimal representation of all the frames in a video shot. The retrieval performance of this representation scheme is further improved by considering the k pixel values with the largest probabilities of occurrence and the highest peaks of the probability distribution of occurrence at each pixel position for a video shot. The corresponding schemes are called k-TMOF and k-pTMOF, respectively. These key frame representation schemes are compared to other histogram-based techniques for video shot representation and retrieval. In the experiments, three video sequences in the MPEG-7 content set were used to evaluate the performances of the different key frame representation schemes. Experimental results show that our proposed representations outperform the alpha-trimmed average histogram for video retrieval.

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