Horror movie scene recognition based on emotional perception

The number of video clips available online is growing at a tremendous pace. Meanwhile, the video scenes of pornography, violence and horror permeate the whole Web. Horror videos, whose threat to children's health is no less than pornographic video, are sometimes neglected by existing Web filtering tools. Consequently, an effective horror video filtering tool is necessary for preventing children from accessing these horror videos. In this paper, by introducing color emotion and color harmony theories, we propose a horror video scene recognition algorithm. Firstly, the video scenes are decomposed into a set of shots. Then we extract the visual features, audio features and color emotion features of each shot. Finally, by combining the three features, the horror video scenes are recognized by the Support Vector Machine (SVM) classifier. According to the experimental results on diverse video scenes, the proposed scheme based on the emotional perception could deal effectively with the horror video scene recognition and promising results are achieved.