Siu Hang Or

About

Siu Hang Or is a researcher in computer vision and robotics, with a focus on 3-D motion estimation from stereo imagery. His major contributions lie in developing model-less, recursive algorithms that recover camera position and orientation from stereo image sequences without requiring prior knowledge of 3-D structures. This approach, based on extended Kalman filters, enables high-speed, robust tracking in dynamic environments. His most-cited work, "Robust 3-D Motion Tracking From Stereo Images: A Model-Less Method" (2008), has garnered 37 citations, demonstrating its influence in the field. A related paper, "Recursive Recovery of Position and Orientation from Stereo Image Sequences without Three-Dimensional Structures" (2006), further advances this methodology, with 10 citations. Or’s research addresses a key limitation of traditional vision-based algorithms, which depend on pre-existing or computed 3-D models, by offering a more flexible and efficient solution. His work is particularly valuable for robotics and autonomous systems, where real-time, model-free tracking is essential.

Research Focus

Key Achievements

Top Papers

1. 1
   Robust 3-D Motion Tracking From Stereo Images: A Model-Less Method

   37 citations · 2008
2. 2
   Recursive Recovery of Position and Orientation from Stereo Image Sequences without Three-Dimensional Structures

   10 citations · 2006

Key Collaborators

Contact & Links