Please use this identifier to cite or link to this item:
|Title:||Hierarchical video summarisation in reference frame subspace|
|Citation:||IEEE Transactions on Consumer Electronics 55(3): 1551-1557, Aug 2009|
|Abstract:||In this paper, a hierarchical video structure summarization approach using Laplacian Eigenmap is proposed, where a small set of reference frames is selected from the video sequence to form a reference subspace to measure the dissimilarity between two arbitrary frames. In the proposed summarization scheme, the shot-level key frames are first detected from the continuity of inter-frame dissimilarity, and the sub-shot level and scene level representative frames are then summarized by using k-mean clustering. The experiment is carried on both test videos and movies, and the results show that in comparison with a similar approach using latent semantic analysis, the proposed approach using Laplacian Eigenmap can achieve a better recall rate in keyframe detection, and gives an efficient hierarchical summarization at sub shot, shot and scene levels subsequently.|
|Appears in Collections:||Electronic and Computer Engineering|
Dept of Electronic and Computer Engineering Research Papers
Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.