Key Clips and Key Frames Extraction of Videos Based on Deep Learning
Junyu Chen, Ganlan Peng, Yuanfang Peng, Mu Fang, Zhibin Chen, Jianqing Li, Liang Lan · Journal of Physics Conference Series · 2021
Abstract The surveillance camera network covering the city, while protecting the safety of people’s lives and property, generate a large amount of surveillance video data every day, but few videos contain useful information. Surveillance cameras in sparsely crowded areas may capture most of the video in the background. A large number of surveillance videos bring greater storage pressure, and also increase the difficulty of the staff’s work. In this paper, we use the auto-encoder network to extract features of video frames. By comparing the feature differences between video frames, we can automatically select key video clips and key frame images that contain useful information to slim down the surveillance video. Through experiments on actual cameras, we found that this method can achieve the purpose of reducing the pressure of storage and traversal.