3D MOTION ESTIMATION OF HAND BASED ON FEATURE POINTS
A new method for estimating 3D motion and structure of finger from 2D image sequence is proposed in this paper. This problem is challenging not only due to the correspondence problem but also the lack of depth cues in 2D image sequence.In this paper, affine motion is chosen as a suitable model for fingers motion. However, the motion model can also be extended and not necessarily be affine. Analysis of intensity images is first used to find the correspondence for each feature point. Then affine motion model is utilized to find the structure and motion parameters. Extensive analysis has been done on how defining appropriate constraints which are necessary for achieving convergence. Finally, experimental results are presented. The results are very encouraging and have many potential applications especially in such fields as gesture recognition, virtual reality, animation and motion tracking.
Tracking estimation Motion model Correspondence Constraint Levenberg-Marquardt method
WEN-QING HUANG HONG-WEI CHEN YUN-HUA ZHANG
College of Biosystem Engineering and Food Science, Zhejiang University, Hangzhou 310029, China;Colle College of Information and Electronics, Zhejiang University of Sciences, Hangzhou 310033, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
3919-3923
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）