Yee Wei Law

Papers

Total Citations

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About

Yee Wei Law is a researcher whose work bridges computer vision, robotics, and wireless networks, with a particular focus on enabling autonomous systems to perceive and interact with dynamic environments. His key research areas include human motion analysis from aerial platforms, connectivity control in wireless robotic networks, and dynamic classifier selection for real-time video processing. Law’s most notable contribution is his work on human pose and path estimation from aerial video using dynamic classifier selection, a method that allows a monocular camera on an unmanned aerial vehicle to estimate human pose and trajectory in near real-time—a challenging problem for robotics and surveillance. This paper has garnered 19 citations, reflecting its relevance to the growing field of aerial robotics. His related work on human motion analysis from UAV video (4 citations) further explores this problem, presenting a preliminary solution for near real-time estimation. Additionally, Law has contributed to the theoretical foundations of wireless robotic networks, proposing a framework for connectivity control and performance optimization (3 citations) that addresses the critical need for maintaining communication links in multi-robot systems. Through these contributions, Law has advanced the practical deployment of autonomous aerial systems in complex, real-world scenarios.