Pattern Recognition to Enhance Video Based Human Identification for Advanced Security - Saravanan, A.; Benschwartz, R.; Roopa, R.; Maheswari, M.; Mohan, K. B. Kishore (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Scholars investigating computer vision are getting more engaged in human acceptance at a distance. In simple terms, gait identification aims to deal with this problem by determining persons solely depending on their gait patterns. This work introduces a spatial-temporal silhouette analysis according to a gait identification system that is both simple and efficient. For any series of images, a background subtraction Initial, the fluctuating silhouettes of a pedestrian individual are differentiated and recorded employing an algorithm and an ordinary correspondence approach. We proposed a pattern recognition methodology that can avoid fraud and precisely identify person silhouettes in videos, even at a distance. CCTV cameras often offer low-quality video, which can make gathering forensic evidence difficult. Online assessments featuring live video have been carried out on a database consisting of 22 unseen pretenders and 50 enrolled human beings. Using an erroneous accept rate of 0.0014, the recommended strategy obtained a 100% verification rate and a 97.8% recognition rate. On the contrary, studies with the Honda/UCSD database were carried out as well and an approximate 99 % identification rate was reached.