In order to improve the accuracy of video anomaly behavior detection,a new detection method based on generative adversarial networks for video foreground areas is proposed.First,the foreground and background masks of the ground truth video frame are extracted,to determine the foreground areas of the output video frames from generative adversarial networks.For the foreground areas under consideration,the foreground area peak signal-to-noise ratio(F-PSNR)is used to calculate the detection score of anomaly behaviors.The experimental results show that the proposed method can effectively improve the detection accuracy of video anomaly behaviors with a reduced detection time for the Avenue dataset,UCSD-Ped1 dataset and UCSD-Ped2 dataset.
关键词
视频异常行为检测/峰值信噪比/生成对抗网络/前景区域
Key words
video anomaly behavior detection/peak signal-to-noise ratio/generative adversarial networks/foreground area
维普
万方数据