Jinxiang Chai

Papers

Total Citations

360

H-Index

About

Jinxiang Chai is a leading researcher in computer graphics and computer vision, with a primary focus on human motion modeling, non-rigid shape reconstruction, and physics-based animation. His most influential contributions include pioneering work on non-rigid shape and motion recovery, where he developed a closed-form solution that elegantly resolves the ambiguities inherent in reconstructing deformable objects from 2D image data. This foundational work, published in 2004 and 2006, has garnered over 330 combined citations and remains a cornerstone for researchers working on structure-from-motion and non-rigid registration. More recently, Chai has tackled the challenging problem of inverse dynamics for human motion, introducing a data-driven approach that overcomes the noise and ambiguity plaguing traditional solutions, particularly during double-stance phases. This 2016 paper, with 30 citations, demonstrates his continued impact on bridging computer graphics with robotics and biomechanics. Chai’s work is characterized by elegant mathematical formulations that yield practical, real-world solutions, making him a highly cited and respected figure in the field.