Video Abstraction Based on Manifold Learning and Mixture Model
基于流形学习和混合模型的视频摘要方法

ion has attracted tremendous attention for its application in video browsing,video indexing,video retrieval and so on.Video abstraction is brief summary of the video content like the text abstraction.In the paper,an automatic method for video abstraction is presented which is based on manifold modeling and mixture model.Manifold modeling is applied to generate the scene manifold of the video,Isomap is used to reduce the dimension of the video frames in larger scenes and the low dimension vectors are put into the mixture model with model selection to complete cluster analysis.Because mixture model with model selection can adapt to the data from any distribution, it is applied to generate the video abstraction automatically.The results from manifold modeling together with those from mixture model constitute the abstraction results.The experiments present the abstraction with less redundance,which demonstrates the effective and efficiency of the proposed method.