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Object-based video synopsis approach using particle swarm optimization

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Abstract

These days surveillance cameras are spreading very fast for security issues; however reviewing, retrieving and analyzing all these surveillance videos consume a lot of time. Video synopsis technology solved this problem by extracting all the active objects tubes that occurred at different times and relocating these objects simultaneously in a video for fast reviewing. Rearranging objects tubes in the video is considered the main challenge in creating video synopsis. Conventional methods proposed different approaches to optimize the energy function for relocating the object, but it suffers from high computational complexity and time-consuming. Moreover, some of these methods could not save the chronological order of moving objects. In this paper, the particle swarm algorithm is proposed for the first time to solve the energy minimization function and rearrange the objects to generate a condensed synopsis video with less collision and in chronological order. The experiments are applied to a benchmark dataset (VIRAT), and the preliminary simulation results demonstrate that the proposed method outperforms the genetic algorithm.

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  1. Computer and Systems Department, Electronics Research Institute, Cairo, Egypt

    Mona M. Moussa & Rasha Shoitan

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  1. Mona M. Moussa
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  2. Rasha Shoitan
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Correspondence to Mona M. Moussa.

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Moussa, M.M., Shoitan, R. Object-based video synopsis approach using particle swarm optimization. SIViP 15, 761–768 (2021). https://doi.org/10.1007/s11760-020-01794-1

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