An optimal key frame representation for video shot retrieval

In this paper, we propose an optimal representation scheme to construct an optimal key frame based on global statistics for video 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 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. Experimental results show that our proposed representations outperform the alpha-trimmed average histogram for video retrieval.