TY  - CONF
AU  - Shanxin Yuan
AU  - Guillermo Garcia-Hernando
AU  - Bjorn Stenger
AU  - Gyeongsik Moon
AU  - Ju Yong Chang
AU  - Kyoung Mu Lee
AU  - Pavlo Molchanov
AU  - Jan Kautz
AU  - Sina Honari
AU  - Liuhao Ge
AU  - Junsong Yuan
AU  - Xinghao Chen
AU  - Guijin Wang
AU  - Fan Yang
AU  - Kai Akiyama
AU  - Yang Wu
AU  - Qingfu Wan
AU  - Meysam Madadi
AU  - Sergio Escalera
AU  - Shile Li
AU  - Dongheui Lee
AU  - Iason Oikonomidis
AU  - Antonis Argyros
AU  - Tae-Kyun Kim
A2  - CVPR
PY  - 2018//
TI  - Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
BT  - 31st IEEE Conference on Computer Vision and Pattern Recognition
SP  - 2636
EP  - 2645
KW  - Three-dimensional displays
KW  - Task analysis
KW  - Pose estimation
KW  - Two dimensional displays
KW  - Joints
KW  - Training
KW  - Solid modeling
N2  - In this paper, we strive to answer two questions: What is the current state of 3D hand pose estimation from depth images? And, what are the next challenges that need to be tackled? Following the successful Hands In the Million Challenge (HIM2017), we investigate the top 10 state-of-the-art methods on three tasks: single frame 3D pose estimation, 3D hand tracking, and hand pose estimation during object interaction. We analyze the performance of different CNN structures with regard to hand shape, joint visibility, view point and articulation distributions. Our findings include: (1) isolated 3D hand pose estimation achieves low mean errors (10 mm) in the view point range of [70, 120] degrees, but it is far from being solved for extreme view points; (2) 3D volumetric representations outperform 2D CNNs, better capturing the spatial structure of the depth data; (3) Discriminative methods still generalize poorly to unseen hand shapes; (4) While joint occlusions pose a challenge for most methods, explicit modeling of structure constraints can significantly narrow the gap between errors on visible and occluded joints.
L1  - http://refbase.cvc.uab.es/files/YGS2018.pdf
UR  - http://dx.doi.org/10.1109/CVPR.2018.00279
N1  - HUPBA; no proj
ID  - Shanxin Yuan2018
ER  -