Detection of Abnormal Crowd Behavior Based on ViBE and Optical Flow Methods

Abstract

AbstractWith the rapid development of computer vision and image processing technology, the detection of abnormal behavior in video has gradually attracted more and more scholars’ attention. This paper proposes a fast method to detect abnormal behavior in surveillance videos. Firstly, the Visual Background Extraction (ViBE) method was used to extract the foreground object. Then, the image speed was separated according to the optical flow method. Finally, the Otsu method was used to binarize the image, the detection effect was evaluated by defining the density of moving pixels in a single frame of image relative to all pixels. In this paper, an experiment with the sudden scattering of concentrated crowds was conducted to simulate crowd abnormal behavior, the results show that the experimental effect is in line with expectations. Compared with other commonly used machine learning methods, the proposed method can be quickly used to detect crowd abnormal behavior in a surveillance video, the detection results can also be quickly evaluated, which has the advantages of low cost and convenience.KeywordsAbnormal behavior detectionViBE methodForeground object extractionOptical flow methodOtsu method