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10 November 2022 Anomaly detection and recognition of video surveillance images based on deep learning
Zehao Bao, Xiancheng Feng, Qi Zhou, Yang Li
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Proceedings Volume 12331, International Conference on Mechanisms and Robotics (ICMAR 2022); 1233138 (2022) https://doi.org/10.1117/12.2652301
Event: International Conference on Mechanisms and Robotics (ICMAR 2022), 2022, Zhuhai, China
Abstract
In order to solve the problems of pool generalization ability of traditional algorithms and high cost of manual inspection for abnormal image detection in remote video surveillance, this paper proposes an algorithm for abnormal image detection in video surveillance based on deep learning. First, the convolutional neural network based on VGG-16 uses the he_normal method to initialize the weights, and then the self-made datasets is preprocessed and input into the convolutional neural network for training, and finally an image for detecting video surveillance is obtained Model of abnormal interference. Experimental results show that this method can detect abnormal interference such as overexposure of brightness, color distortion, and video freezes in video surveillance, with an accuracy rate of 86%.
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Zehao Bao, Xiancheng Feng, Qi Zhou, and Yang Li "Anomaly detection and recognition of video surveillance images based on deep learning", Proc. SPIE 12331, International Conference on Mechanisms and Robotics (ICMAR 2022), 1233138 (10 November 2022); https://doi.org/10.1117/12.2652301
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KEYWORDS
Video surveillance
Image processing
Convolutional neural networks
Convolution
Neural networks
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