Time-Embedding 2D Locality Preserving Projection for Video Summarization
Maosheng Fu, Daming Zhang, Min Kong, Bin Luo · 2008
In this paper we present an effective approach to creating quality video summarization. Considering the video frame sequence and visual similarity, we defined a novel distance formula, which is equivalent to Euclidean distance in respect of norm. A time embedding two dimensional locality preserving projection (TE-2DLPP) is proposed. Experiments show that the new algorithm has better time performance. From the resulting frame cluster, a summary storyboard of the video is created in TE-2DLPP feature subspace, and the obtained experimental results are encouraging.