Spatio-temporal grouping with constraint for seam carving in video summary application

Efficient tools to perform video summarization become essential as the number of cameras for video surveillance is growing exponentially. The development of automatic algorithms to aid human operators in identifying what is important and keeping it in a video summary becomes essential. This paper proposes a new way to obtain video summary based on seam carving. An efficient spatio-temporal grouping is done to determine the temporal rate of reduction depending on the content, to suppress groups of isolated seams, to identify spatio-temporal groups of seams and to approximate by constant segments the number of seams for each group, while keeping the total sum of seams constant. Problems of geometric distortion, anachronism and length of summary have been successfully addressed. The approach has been tested on video sequences of road traffic and leads to good visual results.