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Automatic annotation for film and Television drama shots and recut system based on face identification
Received date: 2015-11-23
Online published: 2017-06-30
This paper proposes an automatic editing system named Star Cut based on face recognition using deep learning and a video shot detection technique. The purpose is to establish a system for management, retrieval, and automatic recut of film and TV shots. First, the system with over 350 faces of pop stars and actors using a U-face model is trained to learn facial features. The system uses the change rate of edges to detect shot edge. After shot segmentation, the system uses the pre-trained face models to identify faces in the input film or TV drama shot by shot. Users can either choose to recognize all figures in these shots or just choose selected one to recut all the shots containing him/her together automatically. The recall rate of shot segmentation is above 95%, and the recognition rate of faces in an shooting angle of 45° is 92.45%. Test results show that the proposed system has good robustness.
Key words: deep learning; face identification; shot segmentation; face detection
LANG Yue1, ZHOU Jiting1, LIANG Xiaolong2, ZHANG Wenjun1 . Automatic annotation for film and Television drama shots and recut system based on face identification[J]. Journal of Shanghai University, 2017 , 23(3) : 353 -363 . DOI: 10.12066/j.issn.1007-2861.1713
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