Communications of the ACM
CLARANS: A Method for Clustering Objects for Spatial Data Mining
IEEE Transactions on Knowledge and Data Engineering
VISTO: visual storyboard for web video browsing
Proceedings of the 6th ACM international conference on Image and video retrieval
STIMO: STIll and MOving video storyboard for the web scenario
Multimedia Tools and Applications
A novel tool for summarization of arthroscopic videos
Multimedia Tools and Applications
Motion-focusing key frame extraction and video summarization for lane surveillance system
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
VSUMM: A mechanism designed to produce static video summaries and a novel evaluation method
Pattern Recognition Letters
Effective summarization of large-scale web images
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Image collection summarization via dictionary learning for sparse representation
Pattern Recognition
Medical Video Summarization using Central Tendency-Based Shot Boundary Detection
International Journal of Computer Vision and Image Processing
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In this paper, we propose a video summarization algorithm by multiple extractions of key frames in each shot. This algorithm is based on the k-medoid clustering algorithms to find the best representative frame for each video shot. This algorithm, which is applicable to all types of descriptors, consists of extracting key frames by similarity clustering according to the given index. In our proposal, the distance between frames is calculated using a fast full search block matching algorithm based on the frequency domain. The proposed approach is computationally tractable and robust with respect to sudden changes in mean intensity within a shot. Additionally, this approach produces different key frames even in the presence of large motion. The experiments results show that our algorithm extracts multiple representatives frames in each video shot without visual redundancy, and thus it is an effective tool for video indexing and retrieval.