SURVEILLANCE SYSTEM FOR REAL TIMES HIGH PRECISION RECOGNITION OF CRIMINAL FACES WILD VIDEOS

Authors

  • Mr.K.Tulasiram, K. HARINI, P. RASAGNYA, K. BHAVANA

Keywords:

Surveillance system, face recognition, criminal detection, deep learning, real-time recognition, video analysis, computer vision.

Abstract

Surveillance systems are crucial in modern society for maintaining safety and security. A high-precision criminal face recognition system capable of operating in real-time under challenging conditions, such as wild video footage, presents significant technical hurdles. This paper proposes a comprehensive approach to a surveillance system aimed at achieving high-precision recognition of criminal faces in real-time video data. The proposed system integrates advanced computer vision techniques with deep learning algorithms to address challenges such as low image quality,

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References

Taigman, Y., et al. (2014). "DeepFace: Closing the gap to human-level performance in face verification." CVPR. 2. Zhao, L., et al. (2018). "Hybrid deep learning for face recognition in motion blur." IEEE Transactions on Image Processing, 27(5).

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Published

2023-12-24

How to Cite

Mr.K.Tulasiram, K. HARINI, P. RASAGNYA, K. BHAVANA. (2023). SURVEILLANCE SYSTEM FOR REAL TIMES HIGH PRECISION RECOGNITION OF CRIMINAL FACES WILD VIDEOS. Pegem Journal of Education and Instruction, 13(4), 497–503. Retrieved from https://pegegog.net/index.php/pegegog/article/view/4012

Issue

Vol. 13 No. 4 (2023): PEGEGOG

Section

Article

License

Creative Commons License

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