TY - GEN
T1 - A Novel Framework of Hand Localization and Hand Pose Estimation
AU - Che, Yunlong
AU - Song, Yuxiang
AU - Qi, Yue
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5
Y1 - 2019/5
N2 - In this paper, we propose a novel framework for hand localization and pose estimation from a single depth image. For hand localization, unlike most existing methods that using heuristic strategies, e.g. color segmentation, we propose Hierarchical Hand location Networks (HHLN) to estimate the hand location from coarse to fine in depth images, which is robust to the complex environment and efficient. It first applied at a low-resolution octree of the whole depth image and produced coarse hand region and then constructs the hand region into a high-resolution octree for fine location estimation. For pose estimation, we propose Wide Receptive-filed (WR-OCNN) which is able to capture meaningful hand structure in different scales and estimate the 3D hand pose accurately. Experiments on two widely-used hand datasets(NYU dataset and ICVL dataset) demonstrate the effectiveness and superiority of the proposed framework.
AB - In this paper, we propose a novel framework for hand localization and pose estimation from a single depth image. For hand localization, unlike most existing methods that using heuristic strategies, e.g. color segmentation, we propose Hierarchical Hand location Networks (HHLN) to estimate the hand location from coarse to fine in depth images, which is robust to the complex environment and efficient. It first applied at a low-resolution octree of the whole depth image and produced coarse hand region and then constructs the hand region into a high-resolution octree for fine location estimation. For pose estimation, we propose Wide Receptive-filed (WR-OCNN) which is able to capture meaningful hand structure in different scales and estimate the 3D hand pose accurately. Experiments on two widely-used hand datasets(NYU dataset and ICVL dataset) demonstrate the effectiveness and superiority of the proposed framework.
KW - Hand Location
KW - Hand Pose Estimation
KW - Octree-based CNN
UR - https://www.scopus.com/pages/publications/85068985325
U2 - 10.1109/ICASSP.2019.8682382
DO - 10.1109/ICASSP.2019.8682382
M3 - 会议稿件
AN - SCOPUS:85068985325
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2222
EP - 2226
BT - 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Y2 - 12 May 2019 through 17 May 2019
ER -