Camera attention weighted strategy for video shot grouping
Fan Jiang, Yu‐Jin Zhang · 2005
Video shot clustering based on visual feature extraction is an important and challenging task in video browsing and retrieval systems. We propose in this paper a novel method for video shot grouping directly processed in MPEG domain. This method places emphasis on extracting shot features in a way that reflects viewer's actual visual perception. In particular, a spatio-temporal human attention model is constructed. Spatially, each frame is split into two areas, attention region and background, indicating two independent parts of viewer's attention: interest of a dominant motive region and a global impression of the surroundings. Temporally, a weighted color histogram is used to emulate human attention affected by camera motion. With this camera attention weighted strategy, a set of shot similarity measures are constructed. Shot grouping based on these similarities achieve promising results in our experiments on MPEG-7 test videos.