English

Interactive Hand Pose Estimation: Boosting accuracy in localizing extended finger joints

Computer Vision and Pattern Recognition 2018-07-26 v2 Human-Computer Interaction

Abstract

Accurate 3D hand pose estimation plays an important role in Human Machine Interaction (HMI). In the reality of HMI, joints in fingers stretching out, especially corresponding fingertips, are much more important than other joints. We propose a novel method to refine stretching-out finger joint locations after obtaining rough hand pose estimation. It first detects which fingers are stretching out, then neighbor pixels of certain joint vote for its new location based on random forests. The algorithm is tested on two public datasets: MSRA15 and ICVL. After the refinement stage of stretching-out fingers, errors of predicted HMI finger joint locations are significantly reduced. Mean error of all fingertips reduces around 5mm (relatively more than 20%). Stretching-out fingertip locations are even more precise, which in MSRA15 reduces 10.51mm (relatively 41.4%).

Keywords

Cite

@article{arxiv.1804.00651,
  title  = {Interactive Hand Pose Estimation: Boosting accuracy in localizing extended finger joints},
  author = {Cairong Zhang and Guijin Wang and Hengkai Guo and Xinghao Chen and Fei Qiao and Huazhong Yang},
  journal= {arXiv preprint arXiv:1804.00651},
  year   = {2018}
}

Comments

Original publication available on https://doi.org/10.2352/ISSN.2470-1173.2018.2.VIPC-251

R2 v1 2026-06-23T01:11:52.681Z