Browsing and Similarity Searching Method for Videos Based on Cluster Analysis
Seiji Hotta, Senya Kiyasu, Sueharu Miyahara · The Journal of The Institute of Image Information and Television Engineers · 2005
We developed a browsing and similarity searching method for videos based on cluster analysis. First, videos are segmented into shots by fuzzy clustering of graph spectral methods. Second, the videos are represented as a sequence of symbols by grouping together shots. According to this representation, the directed graph of videos is formed based on the relationship between these symbols. Initial and terminal shots are extracted from the di-rected graph using fuzzy cluster extraction. The shots can be browsed from the initial shots to the terminal ones sequentially. Selected shots are used as a query video on similarity searches. The performance of the proposed method was evaluated using a video dataset from NASA.