Nilesh Kumar Mishra
Papers
2
Total Citations
4
H-Index
2
About
Nilesh Kumar Mishra is a computer vision researcher specializing in real-time object tracking on embedded platforms. His work focuses on overcoming fundamental challenges in visual tracking, particularly the limitations of particle filters under occlusion and the computational constraints of ARM-based systems. Mishra’s most cited contributions include the development of a hybrid tracking algorithm that integrates Particle Filter and Local Search methods, implemented on the BeagleBoard-xM platform, achieving real-time performance for continuous scene monitoring. He further advanced the field by proposing a hybrid model combining Particle Filter and Kalman Filter to specifically address occlusion handling—a critical weakness in standard particle filter approaches. While his published work has garnered modest citation counts (2 citations each), these papers represent foundational efforts in embedded vision systems, demonstrating how sophisticated tracking algorithms can be optimized for low-power, resource-constrained devices. Mishra’s research bridges theoretical computer vision with practical embedded implementation, offering valuable insights for students and researchers working on autonomous systems, surveillance, or robotics where real-time, occlusion-robust tracking on portable hardware is essential.
Research Focus
Key Achievements
Top Papers
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- 2