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Recognition of suspicious behavior using case-based reasoning

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Abstract

A novel method case-based reasoning was proposed for suspicious behavior recognition. The method is composed of three departs: human behavior decomposition, human behavior case representation and case-based reasoning. The new approach was proposed to decompose behavior into sub-behaviors that are easier to recognize using a saliency-based visual attention model. New representation of behavior was introduced, in which the sub-behavior and the associated time characteristic of sub-behavior were used to represent behavior case. In the process of case-based reasoning, apart from considering the similarity of basic sub-behaviors, order factor was proposed to measure the similarity of a time order among the sub-behaviors and span factor was used to measure the similarity of duration time of each sub-behavior, which makes the similarity calculations more rational and comprehensive. Experimental results show the effectiveness of the proposed method in comparison with other related works and can run in real-time for the recognition of suspicious behaviors.

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Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, Changsha, 410075, China

    Li-min Xia  (夏利民), Bao-juan Yang  (杨宝娟) & Hong-bin Tu  (涂宏斌)

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  1. Li-min Xia  (夏利民)
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  2. Bao-juan Yang  (杨宝娟)
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  3. Hong-bin Tu  (涂宏斌)
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Corresponding author

Correspondence to Li-min Xia  (夏利民).

Additional information

Foundation item: Project(50808025) supported by the National Natural Science Foundation of China; Project(2013GK3012) supported by the Science and Technology Project of Hunan Province, China

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Xia, Lm., Yang, Bj. & Tu, Hb. Recognition of suspicious behavior using case-based reasoning. J. Cent. South Univ. 22, 241–250 (2015). https://doi.org/10.1007/s11771-015-2515-9

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  • DOI: https://doi.org/10.1007/s11771-015-2515-9

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