Efficient 3D Hand Posture Estimation with Self-Occlusion from Multiview Images
Automatic initialization of human hand posture is an important task in human-machine interaction systems using hand gesture. We present a part-based 3D hand posture estimation approach which combines top-down with bottom-up approaches. We use a factor graphical structure model to inference hand pose with selfocclusions. The location probability distribution of each part is determined by evaluating appropriate likelihood. To reduce a heavy computation burden caused by enormous size of each part state spaces, we use genetic algorithm to prune the low likelihood state of each part. Our experimental evaluation demonstrates that improvements of inference optimization efficiency can be obtained with the proposed approach.
hand posture self-occlusion belief propagation genetic aglorithm factor graph
LV Zhiguo LI Yan
School of Mechatronics Engineering&Automation National University of Defense Technology Changsha,Chi State Key Laboratory of Virtual Reality Technology Beihang University Beijing,China
国际会议
南京
英文
143-146
2010-08-26（万方平台首次上网日期，不代表论文的发表时间）