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A Personalized Video Synopsis Framework for Spherical Surveillance Video

S. Priyadharshini*, Ansuman Mahapatra

Department of Computer Science and Engineering, National Institute of Technology Puducherry, India

* Corresponding Author: S. Priyadharshini. Email: email

Computer Systems Science and Engineering 2023, 45(3), 2603-2616.


Video synopsis is an effective way to easily summarize long-recorded surveillance videos. The omnidirectional view allows the observer to select the desired fields of view (FoV) from the different FoV available for spherical surveillance video. By choosing to watch one portion, the observer misses out on the events occurring somewhere else in the spherical scene. This causes the observer to experience fear of missing out (FOMO). Hence, a novel personalized video synopsis approach for the generation of non-spherical videos has been introduced to address this issue. It also includes an action recognition module that makes it easy to display necessary actions by prioritizing them. This work minimizes and maximizes multiple goals such as loss of activity, collision, temporal consistency, length, show, and important action cost respectively. The performance of the proposed framework is evaluated through extensive simulation and compared with the state-of-art video synopsis optimization algorithms. Experimental results suggest that some constraints are better optimized by using the latest metaheuristic optimization algorithms to generate compact personalized synopsis videos from spherical surveillance videos.


Cite This Article

APA Style
Priyadharshini, S., Mahapatra, A. (2023). A personalized video synopsis framework for spherical surveillance video. Computer Systems Science and Engineering, 45(3), 2603-2616.
Vancouver Style
Priyadharshini S, Mahapatra A. A personalized video synopsis framework for spherical surveillance video. Comput Syst Sci Eng. 2023;45(3):2603-2616
IEEE Style
S. Priyadharshini and A. Mahapatra, "A Personalized Video Synopsis Framework for Spherical Surveillance Video," Comput. Syst. Sci. Eng., vol. 45, no. 3, pp. 2603-2616. 2023.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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