Papers
1
Total Citations
3
H-Index
1
About
Weiye Xu is a researcher whose work lies at the intersection of computer vision and robotics, with a particular focus on improving human-robot interaction in indoor environments. His key contributions center on image segmentation techniques for pedestrian detection and trajectory prediction, addressing the critical challenge of accurately measuring distances between mobile robots and humans. In his notable 2023 paper, "An H-GrabCut Image Segmentation Algorithm for Indoor Pedestrian Background Removal," Xu developed an innovative approach to extract pedestrians as regions of interest, effectively mitigating common issues that lead to inaccurate distance measurements in dynamic indoor settings. This work, which has garnered early citations, demonstrates his commitment to enhancing the safety and reliability of autonomous mobile robots operating in human-populated spaces. By refining how robots perceive and track pedestrians, Xu's research lays important groundwork for more intuitive and safer human-robot collaboration, making his contributions particularly valuable for students and researchers working at the intersection of computer vision, robotics, and autonomous navigation.
Research Focus
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Top Papers
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