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Real-World Security Applications Through Computer Vision
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Author(s): Asish Kumar Dalai (VIT-AP University, India)and Hitesh Mohapatra (School of Computer Engineering, Kalinga Institute of Industrial Technology (Deemed), Bhubaneswar, India)
Copyright: 2025
Pages: 24
Source title:
Forensic Intelligence and Deep Learning Solutions in Crime Investigation
Source Author(s)/Editor(s): Christian Kaunert (Dublin City University, Ireland), Anjali Raghav (Sharda University, India), Kamalesh Ravesangar (Tunku Abdul Rahman University of Management and Technology, Malaysia)and Bhupinder Singh (Sharda University, India)
DOI: 10.4018/979-8-3693-9405-2.ch013
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Abstract
The model is trained on a diverse dataset that includes various scenarios of violent interactions, allowing it to perform consistently across different surveillance environments and adapt to changing conditions. The chapter details the training process, including the data augmentation techniques employed to improve the model's generalization. Additionally, the system incorporates behavioral analysis to minimize false positives, helping to differentiate between brief aggressive actions and normal behavior. Extensive testing using real-world surveillance footage demonstrates the system's accuracy in detecting and classifying violent events. Comparative analysis shows that the solution outperforms existing methods in terms of both precision and recall. The chapter also explores the practical implications of deploying such a system, including its scalability for large monitoring networks and its potential integration with existing security infrastructures.
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