Conditional autoregressive-tunicate swarm algorithm based generative adversarial network for violent crowd behavior recognition
Violent crowd behavior detection has gained significant attention in the computer vision system. Diverse crowd behavior detection approaches are introduced to detect violent behavior but enhancing the recognition rate poses a complex task due to different crowd diversity, mutual occlusion between cr...
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| Published in | The Artificial intelligence review Vol. 56; no. Suppl 2; pp. 2099 - 2123 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Dordrecht
Springer Netherlands
01.11.2023
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0269-2821 1573-7462 |
| DOI | 10.1007/s10462-023-10571-8 |
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| Abstract | Violent crowd behavior detection has gained significant attention in the computer vision system. Diverse crowd behavior detection approaches are introduced to detect violent behavior but enhancing the recognition rate poses a complex task due to different crowd diversity, mutual occlusion between crowds, and diversity of monitoring scene. Therefore, a crowd behavior recognition mechanism is introduced by Conditional Autoregressive-Tunicate Swarm Algorithm based Generative Adversarial Network (CA-TSA based GAN) to detect violent behavior. Accordingly, the developed CA-TSA is modeled by inheriting Conditional Autoregressive Value at Risk by Regression Quantiles with Tunicate Swarm Algorithm. Initially, the features, such as Tanimoto based Violence Flows descriptor, Local Ternary patterns, and Gray level co-occurrence matrix are extracted from the video frames. Then, the crowd behavior recognition is done by the GAN, which finds the abnormal and the normal crowd behaviors. Here, GAN is trained by the proposed CA-TSA. Moreover, the performance of the proposed method is analyzed using ASLAN challenge dataset. The developed model has the accuracy, sensitivity, and specificity values of 93.688%, 94.261%, and 94.051%, respectively. |
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| AbstractList | Violent crowd behavior detection has gained significant attention in the computer vision system. Diverse crowd behavior detection approaches are introduced to detect violent behavior but enhancing the recognition rate poses a complex task due to different crowd diversity, mutual occlusion between crowds, and diversity of monitoring scene. Therefore, a crowd behavior recognition mechanism is introduced by Conditional Autoregressive-Tunicate Swarm Algorithm based Generative Adversarial Network (CA-TSA based GAN) to detect violent behavior. Accordingly, the developed CA-TSA is modeled by inheriting Conditional Autoregressive Value at Risk by Regression Quantiles with Tunicate Swarm Algorithm. Initially, the features, such as Tanimoto based Violence Flows descriptor, Local Ternary patterns, and Gray level co-occurrence matrix are extracted from the video frames. Then, the crowd behavior recognition is done by the GAN, which finds the abnormal and the normal crowd behaviors. Here, GAN is trained by the proposed CA-TSA. Moreover, the performance of the proposed method is analyzed using ASLAN challenge dataset. The developed model has the accuracy, sensitivity, and specificity values of 93.688%, 94.261%, and 94.051%, respectively. |
| Author | Singh, Juginder Pal Kumar, Manoj |
| Author_xml | – sequence: 1 givenname: Juginder Pal surname: Singh fullname: Singh, Juginder Pal email: juginder.singh@gla.ac.in organization: Department of Computer Engineering & Applications, GLA University – sequence: 2 givenname: Manoj surname: Kumar fullname: Kumar, Manoj organization: Department of Computer Engineering & Applications, GLA University |
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| CitedBy_id | crossref_primary_10_1007_s10462_024_10786_3 crossref_primary_10_1007_s11831_025_10228_5 crossref_primary_10_1016_j_engappai_2024_109559 crossref_primary_10_3390_electronics13244925 |
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| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Copyright Springer Nature B.V. Nov 2023 |
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| Keywords | Tunicate Swarm Algorithm (TSA) Video surveillance Crowd behavior analysis Generative Adversarial Networks (GAN) Violent behavior recognition |
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| Title | Conditional autoregressive-tunicate swarm algorithm based generative adversarial network for violent crowd behavior recognition |
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