An optimized complex motion prediction approach based on a video synopsis

Abstract

PurposeThe space-time variants algorithm will not give good results in practical scenarios; when no tubes increase, these techniques will not give the results. It is challenging to reduce the energy of the output synopsis videos. In this paper, a new optimized technique has been implemented that models and covers every frame in the output video.Design/methodology/approachIn the video synopsis, condensing a video to produce a low frame rate (FR) video using their spatial and temporal coefficients is vital in complex environments. Maintaining a database is also feasible and consumes space. In recent years, many algorithms were proposed.FindingsThe main advantage of this proposed technique is that the output frames are selected by the user definitions and stored in low-intensity communication systems and also it gives tremendous support to the user to select desired tubes and thereby stops the criterion in the output video, which can be further suitable for the user's knowledge and creates nonoverlapping tube-oriented synopsis that can provide excellent visual experience.Research limitations/implicationsIn this research paper, four test videos are utilized with complex environments (high-density objects) and show that the proposed technique gives better results when compared to other existing techniques.Originality/valueThe proposed method provides a unique technique in video synopsis for compressing the data without loss.