An video shot segmentation scheme based on adaptive binary searching and SIFT

Authors:
Xinghao Jiang;Tanfeng Sun;Jin Liu;Wensheng Zhang;Juan Chao
Affiliations:
School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, China;School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, China;State Key Lab. of Software Engineering, School of Computer, Wuhan University, Wuhan, China;Key Lab. of Complex System & Intelligence Science, Institute of Automation, Chinese Academy of Science, Beijing, China;School of Information Security Engineering, Shanghai Jiao Tong University, Shanghai, China
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

A video shot segmentation scheme with dual-detection model is proposed. In the pre-detection round, the Uneven Blocked differences are presented and used in Adaptive Binary Search (ABS) to detect shot boundaries. In the re-detection round, the Scale Invariant Feature Transform (SIFT) method is applied to exclude false detections. Experiments show that this algorithm achieves well performances in detecting both abrupt and gradual boundaries.