Video partitioning by segmenting moving object trajectories
Tapas Badal, Neeta Nain, Mushtaq Ahmed · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
Video partitioning may be involve in a number of applications and present solutions for monitoring and tracking particular person trajectory and also helps in to generate semantic analysis of single entity or of entire video. Many recent advances in object detection and tracking concern about motion structure and data association used to be assigned a label to trajectories and analyze them independently. In this work we propose an approach for video portioning and a structure is given to store motion structure of target set to monitor in video. Spatio-temporal tubes separate individual objects that help to generate semantic analysis report for each object individually. The semantic analysis system for video based on this framework provides not only efficient synopsis generation but also spatial collision where the temporal consistency can be resolved for representation of semantic knowledge of each object. For keeping low computational complexity trajectories are generated online and classification, knowledge representation and arrangement over spatial domain are suggested to perform in offline manner.