Changhai Xu

Papers

Total Citations

H-Index

About

Changhai Xu is a leading researcher in embodied computer vision and autonomous robotic perception, with a primary focus on real-time scene understanding and motion-based segmentation. His seminal work, "Real-time indoor scene understanding using Bayesian filtering with motion cues" (2011, 65 citations), introduced a pioneering method enabling an embodied agent to efficiently model indoor environments by leveraging motion cues and generic geometric knowledge. This approach allows robots to build dynamic spatial models from their own movement experience, significantly advancing autonomous navigation. Xu further contributed to motion segmentation by developing techniques that exploit the correlation between a robot's motor signals and background motion, as demonstrated in "Motion Segmentation by Learning Homography Matrices from Motor Signals" (2011, 8 citations) and "Moving Object Segmentation Using Motor Signals" (2012, 6 citations). His work uniquely integrates motor control signals with visual perception to separate foreground objects from static backgrounds, offering a robust solution for dynamic environments. Xu's research has profound implications for robotics, particularly in autonomous systems requiring real-time environmental understanding and object tracking. His innovative use of Bayesian filtering and motor-visual coupling continues to inspire advances in intelligent robotic perception.