提出了一种利用视频序列的自适应时间片梯度谱对镜头转换类型进行精细识别的算法.在这个算法中，首先提出了自适应时间片梯度谱的概念，并且在此基础上，提出了用于识别镜头转换类型的模板构造和匹配算法，同时还给出了一种描述语言作为模板的软描述方法，用以适应不同的图象尺寸和镜头转换的持续时间.实验结果表明，这种方法在多数情况下具有很好的识别效果，只是在两个镜头转换非常相近时，识别效果差些，另外，该方法识别速度快，同时具有很强的鲁棒性和可扩展性，是解决镜头转换类型精细识别问题的一个有益尝试

In this paper, a series of techniques are developed to address this problem. First, a new concept, adaptive gradient slice(AGS), is defined for the purpose of transforming a 3D video sequence to a 2D representation. Then image projection and morphological operations are adopted to locate shot transitions in the AGS domain. For the detected transitions, soft templates and corresponding template-matching algorithms are designed to recognize their fine structures. Simulation results show that, with the manually constructed templates, the proposed algorithm can recognize most of the transitions in the experiment very precisely in real time. Only for two transitions quite similar to each other, the proposed algorithm will encounter some difficulties to distinguish them. The reason is that the mapping from 3D sequence to 2D image loses some spatial information. However. In conclusion, this paper provides an effective way to deal with the problem of fine structure recognition of video shot transitions.