Nabin Sharma Rijal
Papers
2
Total Citations
4
H-Index
2
About
Nabin Sharma Rijal is a computer vision researcher specializing in real-time object tracking on embedded systems. His work focuses on developing robust tracking algorithms that can operate efficiently on resource-constrained ARM-based platforms like the BeagleBoard-xM. Rijal’s major contributions include hybridizing Particle Filters with Local Search algorithms to achieve intelligent, continuous target tracking in dynamic scenes, and integrating Kalman Filters to handle occlusion—a critical challenge where standard particle filters fail. His most-cited papers, both from 2014, each have garnered 2 citations, establishing foundational work in embedded vision systems. By addressing the dual constraints of real-time performance and limited computational power, Rijal’s research bridges the gap between theoretical tracking methods and practical deployment on low-cost hardware. His innovations in occlusion handling and local search optimization have implications for autonomous robotics, surveillance, and mobile vision applications, making his work a valuable reference for students and researchers developing efficient computer vision solutions for embedded platforms.
Research Focus
Key Achievements
Top Papers
- 1
- 2