Amar Mani Aryal
Papers
2
Total Citations
4
H-Index
2
About
Amar Mani Aryal is a researcher specializing in embedded computer vision and real-time object tracking. His work focuses on developing efficient, hybrid tracking algorithms for resource-constrained platforms, particularly ARM-based embedded systems like the BeagleBoard-xM. Aryal's major contributions include the implementation of a Real Time Local Search Particle Filter, which enhances the standard Particle Filter by integrating a local search mechanism for more intelligent and accurate target tracking. He also pioneered a Hybrid Model combining Particle Filter and Kalman Filter to specifically address the critical challenge of occlusion, where a tracked object is temporarily hidden from view. While his most-cited papers each hold 2 citations, these works represent foundational efforts in bringing sophisticated computer vision techniques to low-power, real-time embedded devices, a crucial step for applications like autonomous drones and robotics. Aryal's research demonstrates a practical engineering approach to solving complex tracking problems, bridging the gap between theoretical algorithms and real-world deployment on limited hardware.
Research Focus
Key Achievements
Top Papers
- 1
- 2