Shot retrieval based on fuzzy evolutionary aiNet and hybrid features

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2011
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Li, Xiang-Hui
Zhan, Yong-Zhao
Ke, Jia
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Computers in Human Behavior. 2011, 27(5), pp. 1571-1578. ISSN 0747-5632. Available under: doi: 10.1016/j.chb.2010.11.002
Zusammenfassung

As the multimedia data increasing exponentially, how to get the video data we need efficiently become so important and urgent. In this paper, a novel method for shot retrieval is proposed, which is based on fuzzy evolutionary aiNet and hybrid features. To begin with, the fuzzy evolutionary aiNet algorithm proposed in this paper is utilized to extract key-frames in a video sequence. Meanwhile, to represent a key-frame, hybrid features of color feature, texture feature and spatial structure feature are extracted. Then, the features of key-frames in the same shot are taken as an ensemble and mapped to high dimension space by non-linear mapping, and the result obeys Gaussian distribution. Finally, shot similarity is measured by the probabilistic distance between distributions of the key-frame feature ensembles for two shots, and similar shots are retrieved effectively by using this method. Experimental results show the validity of this proposed method.

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004 Informatik
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Shot retrieval, Fuzzy evolutionary aiNet, Hybrid features, Probabilistic distance, Similarity measure, Key-frame extraction
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Zitieren
ISO 690LI, Xiang-Hui, Yong-Zhao ZHAN, Jia KE, Hongwei ZHENG, 2011. Shot retrieval based on fuzzy evolutionary aiNet and hybrid features. In: Computers in Human Behavior. 2011, 27(5), pp. 1571-1578. ISSN 0747-5632. Available under: doi: 10.1016/j.chb.2010.11.002
BibTex
@article{Li2011retri-16627,
  year={2011},
  doi={10.1016/j.chb.2010.11.002},
  title={Shot retrieval based on fuzzy evolutionary aiNet and hybrid features},
  number={5},
  volume={27},
  issn={0747-5632},
  journal={Computers in Human Behavior},
  pages={1571--1578},
  author={Li, Xiang-Hui and Zhan, Yong-Zhao and Ke, Jia and Zheng, Hongwei}
}
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