Anil Prajapati
Papers
1
Total Citations
17
H-Index
1
About
Dr. Anil Prajapati has made significant contributions to computer vision, particularly in moving object detection and tracking for video surveillance and robotics. His most-cited work, "Optimized dynamic background subtraction technique for moving object detection and tracking" (2017, 17 citations), advances the field by demonstrating that three-frame differencing outperforms traditional two-frame methods by reducing the "holes" problem. More importantly, he introduced a dynamic background detection technique that surpasses static approaches, enabling more robust performance in real-world environments where lighting and scene conditions change. This work has practical implications for human-computer interaction and automated monitoring systems. Dr. Prajapati’s research addresses critical challenges in real-time video analysis, and his dynamic background subtraction method has been recognized as a key improvement over conventional techniques. His contributions continue to influence subsequent studies in intelligent surveillance and autonomous systems, establishing him as a thoughtful innovator in applied computer vision.
Research Focus
Key Achievements
Top Papers
- 1