Key frame extraction based on evolutionary artificial immune network

Authors:
Fang Liu;Xiaoying Pan
Affiliations:
School of Computer Science and Engineering, Xidian University, Xi’an, China;School of Computer Science and Engineering, Xidian University, Xi’an, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

Citing 2
Cited 0

An Evolutionary Immune Network for Data Clustering

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Efficient Key-Frame Extraction and Video Analysis

ITCC '02 Proceedings of the International Conference on Information Technology: Coding and Computing

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Abstract

Key frame extraction has been recognized as one of the important research issues in video retrieval. Key Frame Extraction based on Evolutionary Artificial Immune Network (KFE-EAIN) is proposed in this paper. To describe the distribution of video frame data, an artificial immune network is first evolved by video frame data. Then, key frame can be selected by minimal spanning tree of the network. KFE-EAIN does not require the number of clusters to be known beforehand. Otherwise, it can apply to both single shot and video sequence. Experimental results show that KFE-EAIN can effectively summarize content of a video with acceptable complexity.