关键词: 动画场景切换, 在线检测, Bayesian决策, 缓存队列

Abstract: Animation scene detection is a fundamental task for many advanced animation video analysis. Traditional detection methods that are based on pixels’ analysis and threshold, may require huge storage and not be robust to noises and normal object motions. Additionally, it is also difficult to define suitable thresholds for complicated animation scenes. A new online animation scene detection method is proposed in this paper. At first, the proposed method segments video frame images into some sub-blocks and calculate their HSV feature values. Then the distance between two consecutive video frames are recorded into a buffer queue with fixed length. Finally, the proposed dynamic Bayesian decision rules are used to determine whether there exists a scene change. The experimental results on several types of real video demonstrate that the new method can gain better performance on detection accuracy and computation efficiency.

Key words: animation scene change, online detection, Bayesian decision, buffer queue