Dynamic key-frame extraction for video summarization
Gianluigi Ciocca, Raimondo Schettini · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
We propose an innovative approach to the selection of representative frames of a video shot for video summarization. By analyzing the differences between two consecutive frames of a video sequence, the algorithm determines the complexity of the sequence in terms of visual content changes. Three descriptors are used to express the frame’s visual content: a color histogram, wavelet statistics and an edge direction histogram. Similarity measures are computed for each descriptor and combined to form a frame difference measure. The use of multiple descriptors provides a more precise representation, capturing even small variations in the frame sequence. This method can dynamically, and rapidly select a variable number of key frame within each shot, and does not exhibit the complexity of existing methods based on clustering algorithm strategies. The method has been tested on various video segments of different genres (trailers, news, animation, etc.) and preliminary results shows that the algorithm is able to effectively summarize the shots capturing the most salient events in the sequences.