Xuedong Wu

Jiangsu University of Science and Technology, Zhejiang University, Zhejiang University of Technology

Papers

Total Citations

184

H-Index

About

Dr. Xuedong Wu is a pioneering researcher whose work bridges computer vision and deep learning, with a particular focus on advancing human-machine interaction. His most impactful contribution, "Facial expression recognition based on deep learning" (2022), has garnered 172 citations, establishing him as a leading voice in affective computing. This work leverages deep neural architectures to decode subtle emotional cues from facial imagery, a critical capability for applications ranging from assistive robotics to behavioral analysis. Earlier in his career, Dr. Wu made foundational contributions to pose and motion estimation, notably through his development of Gaussian and non-Gaussian particle filter methods (2006–2007). These papers, while less cited, solved the long-standing problem of determining 3D position, orientation, and relative motion from monocular image sequences—a challenge central to robotic guidance, manipulation, and photogrammetry. By demonstrating how particle filtering could handle nonlinear, non-Gaussian noise in real-world environments, he provided a robust framework for dynamic vision systems. Dr. Wu’s work thus spans from low-level geometric estimation to high-level semantic interpretation, reflecting a rare depth in both theoretical methodology and applied deep learning. His research continues to inspire new generations of computer vision engineers.