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  • Open Access


    Abnormal Behavior Detection Using Deep-Learning-Based Video Data Structuring

    Min-Jeong Kim1, Byeong-Uk Jeon1, Hyun Yoo2, Kyungyong Chung3,*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2371-2386, 2023, DOI:10.32604/iasc.2023.040310

    Abstract With the increasing number of digital devices generating a vast amount of video data, the recognition of abnormal image patterns has become more important. Accordingly, it is necessary to develop a method that achieves this task using object and behavior information within video data. Existing methods for detecting abnormal behaviors only focus on simple motions, therefore they cannot determine the overall behavior occurring throughout a video. In this study, an abnormal behavior detection method that uses deep learning (DL)-based video-data structuring is proposed. Objects and motions are first extracted from continuous images by combining existing DL-based image analysis models. The… More >

  • Open Access


    An Improved Two-stream Inflated 3D ConvNet for Abnormal Behavior Detection

    Jiahui Pan1,2,*, Liangxin Liu1, Mianfen Lin1, Shengzhou Luo1, Chengju Zhou1, Huijian Liao3, Fei Wang1,2

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 673-688, 2021, DOI:10.32604/iasc.2021.020240

    Abstract Abnormal behavior detection is an essential step in a wide range of application domains, such as smart video surveillance. In this study, we proposed an improved two-stream inflated 3D ConvNet network approach based on probability regression for abnormal behavior detection. The proposed approach consists of four parts: (1) preprocessing pretreatment for the input video; (2) dynamic feature extraction from video streams using a two-stream inflated 3D (I3D) ConvNet network; (3) visual feature transfer into a two-dimensional matrix; and (4) feature classification using a generalized regression neural network (GRNN), which ultimately achieves a probability regression. Compared with the traditional methods, two-stream… More >

  • Open Access


    Abnormal Behavior Detection and Recognition Method Based on Improved ResNet Model

    Huifang Qian1, Xuan Zhou1, *, Mengmeng Zheng1

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2153-2167, 2020, DOI:10.32604/cmc.2020.011843

    Abstract The core technology in an intelligent video surveillance system is that detecting and recognizing abnormal behaviors timely and accurately. The key breakthrough point in recognizing abnormal behaviors is how to obtain the effective features of the picture, so as to solve the problem of recognizing them. In response to this difficulty, this paper introduces an adjustable jump link coefficients model based on the residual network. The effective coefficients for each layer of the network can be set after using this model to further improving the recognition accuracy of abnormal behavior. A convolution kernel of 1×1 size is added to reduce… More >

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