抄録
We propose an automatic and adaptive method to detect relatively important parts in multimedia content.The important parts of content should characterize the whole content and also be regarded as its summary.By applying our method,users capture important screenshots of the content and extract a set of important parts of the content that contain characteristic scenes.To evaluate the importance of the various parts,our method uses the user's viewing history.Numerical experiments show the feasibility of the proposed method.
