An improved surveillance video synopsis framework: a HSATLBO optimization approach

Ghatak, Subhankar; Rup, Suvendu; Majhi, Banshidhar; Swamy, M.N.S.

doi:10.1007/s11042-019-7389-7

Cited by 23 publications

(10 citation statements)

References 40 publications

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“…Ahmed et al [13] presented a methodology for synopsis generation concerning a user's query. Ghatak et al [4] presented a hybridization of Simulated Annealing and Teaching Learning based Optimization algorithms to generate an efficient synopsis video. Ghatak et al [5] suggested an improved optimization scheme using the hybridization of Simulated Annealing and Jaya algorithms for the generation of video synopsis.…”

Section: Non-spherical Synopsis Video Methodsmentioning

confidence: 99%

“…2 summarizes the video synopsis-related works on non-spherical videos. [13] Query based synopsis video Yes No Ghatak et al, 2020 [4] Generation of surveillance video synopsis Yes No Ghatak et al, 2020 [5] Generates consumer surveillance synopsis video Yes No Namitha and Narayanan, 2020 [6] Generates synopsis video with interaction preservation Yes No…”

Section: Non-spherical Synopsis Video Methodsmentioning

confidence: 99%

“…It is solved using various latest optimization algorithms such as Aquila Optimizer (AO) [27], Archimedes Optimization Algorithm (AOA) [28], Dynamic Differential Annealing Optimization (DDAO) [29], Giza Pyramids Construction (GPC) [30], Heap-Based Optimizer (HBO) [31], Hybrid Whale Optimization with Seagull Algorithm (HWSOA) [32] as well as existing works on video synopsis such as Hybrid Simulated Annealing-Jaya (HSAJaya) [5], Hybridization of Simulated Annealing and Teaching Learning based Optimization (HSATLBO) [4], and Simulated Annealing (SA) [1]. The personalized tube rearrangement is given in Algorithm 3.…”

Section: Algorithm 2 Lookupmentioning

confidence: 99%

“…The object-based video synopsis approach is handy to solve this issue. Despite tremendous efforts devoted to the object-based video synopsis on the non-spherical videos [1][2][3][4][5][6], they cannot be directly applied to the spherical videos. Traditionally, 360degree video summarization offers fixed FoV-based summarization, the spherical video summarization in a personalized manner is not focused.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Personalized Video Synopsis Framework for Spherical Surveillance Video

Priyadharshini¹,

Mahapatra²

2023

Computer Systems Science and Engineering

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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.

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Section: Non-spherical Synopsis Video Methodsmentioning

confidence: 99%

Section: Non-spherical Synopsis Video Methodsmentioning

confidence: 99%

Section: Algorithm 2 Lookupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Personalized Video Synopsis Framework for Spherical Surveillance Video

Priyadharshini¹,

Mahapatra²

2023

Computer Systems Science and Engineering

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“…If the difference is higher than a predetermined threshold value, the tubes are consolidated to generate a tube set. Ghatak et al [ 10 ] presented an effort for minimizing activity loss, collision number, and cost of temporal consistency. They proposed an improvement for the energy minimization strategy.…”

Section: Introductionmentioning

confidence: 99%

User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions

Shoitan

Moussa

Gharghory

et al. 2023

Sensors

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During the last decade, surveillance cameras have spread quickly; their spread is predicted to increase rapidly in the following years. Therefore, browsing and analyzing these vast amounts of created surveillance videos effectively is vital in surveillance applications. Recently, a video synopsis approach was proposed to reduce the surveillance video duration by rearranging the objects to present them in a portion of time. However, performing a synopsis for all the persons in the video is not efficacious for crowded videos. Different clustering and user-defined query methods are introduced to generate the video synopsis according to general descriptions such as color, size, class, and motion. This work presents a user-defined query synopsis video based on motion descriptions and specific visual appearance features such as gender, age, carrying something, having a baby buggy, and upper and lower clothing color. The proposed method assists the camera monitor in retrieving people who meet certain appearance constraints and people who enter a predefined area or move in a specific direction to generate the video, including a suspected person with specific features. After retrieving the persons, a whale optimization algorithm is applied to arrange these persons reserving chronological order, reducing collisions, and assuring a short synopsis video. The evaluation of the proposed work for the retrieval process in terms of precision, recall, and F1 score ranges from 83% to 100%, while for the video synopsis process, the synopsis video length compared to the original video is decreased by 68% to 93.2%, and the interacting tube pairs are preserved in the synopsis video by 78.6% to 100%.

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A Comprehensive Investigation About Video Synopsis Methodology and Research Challenges

Jagtap

Chopade

2021

Inventive Computation and Information Technologies

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An improved surveillance video synopsis framework: a HSATLBO optimization approach

Cited by 23 publications

References 40 publications

A Personalized Video Synopsis Framework for Spherical Surveillance Video

A Personalized Video Synopsis Framework for Spherical Surveillance Video

User Preference-Based Video Synopsis Using Person Appearance and Motion Descriptions

A Comprehensive Investigation About Video Synopsis Methodology and Research Challenges

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