摘要
采用三维人手图模型描述了人手结构、运动学、动力学及自遮挡特性,将人手高维(27维)跟踪问题转为并行跟踪16个6维变量的问题,降低了计算复杂度.在非参数信念传播过程中嵌入连续自适应均值漂移方法得到可行C-空间,在该空间中传递消息以提高跟踪效率.实验结果表明,该方法在人手发生自遮挡的情况下,能快速、鲁棒地跟踪关节人手.
We design a pertinence graphical model, combined with domain-specific heuristics among the components of human hand, to describe the hand＇s 3D structure, kinematics, dynamics and self-occlusion. The modular structure facilitates tracking each hand component （sixteen variables of six degrees of freedom） separately instead of tracking hand configuration of 27 degrees of freedom as a while to reduce the computational complexity. Then, a more efficient belief propagation method embedding continuously adaptive mean shift （CAMSHIFT） algorithm to obtain configuration space （C-space） is proposed. Belief propagation is processed in the feasible C-space to increase the tracking efficiency. The experimental results show that our proposed method can track articulated hand robustly and efficiently under self-occlusion.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2008年第4期476-481,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60473049)
国家"八六三"高技术研究发展计划(2006AA01Z120)
关键词
关节人手跟踪
图模型
非参数信念传播
articulated hand tracking
graphical model
nonparametric belief propagation
