Research on Effective Segment Extraction of Ship Surveillance Videos.

Effective segment extraction has broad application prospects in the field of video surveillance. In action recognition or object recognition, a large number of repetitive background segments will reduce the efficiency of computation. This causes the algorithm to consume more time. Effective segments can greatly save computing and storage resources for both target detection and storage. Common algorithms are to process the whole surveillance video, such as frame difference method and optical flow method. However, false detection can occur when the picture is disturbed, such as snowflakes. Will result in low accuracy. The effective segment detection method adopted in this paper. First convert the color space. The surveillance video is then segmented. Features were extracted and repeated segments filtering was carried out to reduce the interference of bad images. Finally, effective segments are extracted. Experimental results show that the accuracy of the effective segment detection method adopted in this paper is increased by more than 50%, and the F-metric value is increased by more than 24%.