Cascaded Hand Pose Regression

Xiao Sun, Yichen Wei, Shuang Liang, Xiaoou Tang, Jian Sun; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 824-832

Abstract


We extends the previous 2D cascaded object pose regression work [9] in two aspects so that it works better for 3D articulated objects. Our first contribution is 3D pose-indexed features that generalize the previous 2D parameterized features and achieve better invariance to 3D transformations. Our second contribution is a principled hierarchical regression that is adapted to the articulated object structure. It is therefore more accurate and faster. Comprehensive experiments verify the state-of-the-art accuracy and efficiency of the proposed approach on the challenging 3D hand pose estimation problem, on a public dataset and our new dataset.

Related Material


[pdf]
[bibtex]
@InProceedings{Sun_2015_CVPR,
author = {Sun, Xiao and Wei, Yichen and Liang, Shuang and Tang, Xiaoou and Sun, Jian},
title = {Cascaded Hand Pose Regression},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}