Yucheng Wei

Chinese Academy of Sciences, Institute of Automation

Papers

Total Citations

300

H-Index

About

Yucheng Wei is a researcher whose work bridges computer vision and robotics, with a particular focus on real-time visual tracking and autonomous navigation. His most influential contribution, "Real-time hand tracking using a mean shift embedded particle filter" (2007), has garnered 230 citations, demonstrating its lasting impact on gesture recognition and human-computer interaction. In this work, Wei pioneered a hybrid approach that integrates mean shift clustering into particle filtering, significantly improving tracking efficiency and robustness under challenging conditions. Earlier, his 2004 paper on mobile robot self-localization introduced a novel method that uses global visual appearance features—encoded as multidimensional histograms of color, edge density, gradient magnitude, and texture—to enable reliable position estimation without relying on landmarks or maps. This work, with 70 citations, laid groundwork for appearance-based localization in robotics. Wei’s contributions are notable for their practical emphasis on real-time performance and computational efficiency, making them valuable for applications in assistive technology, autonomous systems, and interactive environments. His research continues to influence developments in visual tracking and mobile robotics.