An improved tube rearrangement strategy for choice-based surveillance video synopsis generation

Abstract

Video synopsis is a promising technology that offers easy browsing and indexing of surveillance videos. This article presents an improved video synopsis framework, introducing the inclusion of anomalous tube detection module. The suggested framework performs better than the existing methodologies by offering a flexibility to the user to generate a synopsis video, which is based on user's choice of interest. Traditionally, to generate a synopsis video, the object tubes are temporally shifted for achieving compression. The applied temporal shift incurs a large number of collision artifacts along with temporal chronology violation. To address this issue for producing a visually comfortable synopsis video, the collision and temporal chronology violations are amended through Acceleration/Retardation of object's motion and spatial shift. Collision oriented Acceleration/Retardation and Spatial shift strategies are embedded sequentially in the proposed combined algorithm cSAScO. The unified representation of the proposed cSAScO algorithm combines the individual strength of Simulated Annealing (SA) and Scenario Optimization (ScO) and is employed to the formulated choice-based tube rearrangement problem. The efficacy of the proposed scheme is demonstrated through extensive experiments and its performance compared with that of the benchmark schemes.