Detection of Violence Based on Hidden Markov Model

Abstract:

This paper proposes an intelligent video analysis technology for elevator cage abnormality detection in computer vision. By collecting, processing, and analyzing video images in real time, the feature vectors including the variation of foreground pixels, the variation of length and width of foreground region’s enclosing rectangle and the variation of foreground region’s center of mass are obtained. The background is modeled by the Codebook Subtraction algorithm，these feature data are processed via K-Means clustering to get observation sequences, which are used to model a Hidden Markov Model (HMMs) for the normal activity. Last, the abnormalities are identified by the difference, which is predetermined by observing the normal and abnormal activity testing sequences, from normal activity model

• Periodical: Advanced Materials Research (Volumes 433-440)
• Pages: 4651-4655
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.433-440.4651
• Online since: January 2012
• Authors: Hui Qing Lu, Wei Nan Zhu, Yu Chao Zhou
• Keywords: Codebook Subtraction Algorithm, Hidden Markov Model (HMM), Video Images

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