Parashar Dhakal
Papers
2
Total Citations
4
H-Index
2
About
Parashar Dhakal is a researcher specializing in real-time computer vision and embedded systems, with a focus on intelligent object tracking. His major contributions lie in developing hybrid algorithms that enhance the robustness of tracking systems on resource-constrained platforms. Specifically, he pioneered the integration of Particle Filter and Local Search algorithms to achieve efficient, real-time target tracking on ARM-based embedded devices like the BeagleBoard-xM. Additionally, Dhakal addressed a critical limitation of Particle Filters—failure during object occlusion—by designing a hybrid model that combines Particle Filter with Kalman Filter, ensuring continuous and accurate tracking even in complex, cluttered scenes. Although his most-cited works each have 2 citations, they represent foundational efforts in optimizing computer vision for low-power hardware, a growing field for autonomous systems and robotics. His work demonstrates a practical approach to bridging algorithmic theory with real-world deployment, making him a notable contributor to embedded vision research.
Research Focus
Key Achievements
Top Papers
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- 2