Segmentation of video by clustering and graph analysis
Computer Vision and Image Understanding
Determining computable scenes in films and their structures using audio-visual memory models
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Image and Video Databases: Restoration, Watermarking and Retrieval
Image and Video Databases: Restoration, Watermarking and Retrieval
Constructing table-of-content for videos
Multimedia Systems - Special section on video libraries
Video Scene Segmentation via Continuous Video Coherence
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Scene Determination Based on Video and Audio Features
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Systematic evaluation of logical story unit segmentation
IEEE Transactions on Multimedia
Automated high-level movie segmentation for advanced video-retrieval systems
IEEE Transactions on Circuits and Systems for Video Technology
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Time Adaptive Clustering (TAC) is a cognitive Logical Story Unit (LSU) segmentation algorithm that is found to show good and consistent results. This paper presents an efficient hardware implementation for approximating the TAC algorithm. The design consists of three main blocks. The first block generates similarity values needed in the clustering process. To take full advantage of the parallelism of Field Programmable Gate Arrays (FPGA) devices, a video shot sequence is divided into subsets and processed in parallel by the second block. The third block combines all the output results of each subset. The design is implemented on a Xilinx Virtex-II xc2v3000 on board a RC203E board and it runs 27 times faster than a Pentium 4-based PC at 3.4 Ghz.