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Point-to-Pose Voting based Hand Pose Estimation using Residual Permutation Equivariant Layer

Li, Shile and Lee, Dongheui (2019) Point-to-Pose Voting based Hand Pose Estimation using Residual Permutation Equivariant Layer. In: 32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019. IEEE. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), USA. doi: 10.1109/CVPR.2019.01220. ISBN 978-1-7281-3294-5. ISSN 1063-6919.

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Official URL: https://ieeexplore.ieee.org/document/8953716

Abstract

Recently, 3D input data based hand pose estimation methods have shown state-of-the-art performance, because 3D data capture more spatial information than the depth image. Whereas 3D voxel-based methods need a large amount of memory, PointNet based methods need tedious preprocessing steps such as K-nearest neighbour search for each point. In this paper, we present a novel deep learning hand pose estimation method for an unordered point cloud. Our method takes 1024 3D points as input and does not require additional information. We use Permutation Equivariant Layer (PEL) as the basic element, where a residual network version of PEL is proposed for the hand pose estimation task. Furthermore, we propose a voting-based scheme to merge information from individual points to the final pose output. In addition to the pose estimation task, the votingbased scheme can also provide point cloud segmentation result without ground-truth for segmentation. We evaluate our method on both NYU dataset and the Hands2017Challenge dataset, where our method outperforms recent state-of-theart methods.

Item URL in elib:https://elib.dlr.de/132905/
Document Type:Conference or Workshop Item (Lecture)
Title:Point-to-Pose Voting based Hand Pose Estimation using Residual Permutation Equivariant Layer
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Li, ShileTUMUNSPECIFIEDUNSPECIFIED
Lee, DongheuiUNSPECIFIEDhttps://orcid.org/0000-0003-1897-7664UNSPECIFIED
Date:2019
Journal or Publication Title:32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI:10.1109/CVPR.2019.01220
Publisher:IEEE
ISSN:1063-6919
ISBN:978-1-7281-3294-5
Status:Published
Keywords:Hand Pose Estimation, Point-to-Pose Voting, Permutation Equivariant Layer
Event Title:IEEE International Conference on Computer Vision and Pattern Recognition (CVPR)
Event Location:USA
Event Type:international Conference
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Terrestrial Assistance Robotics (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Deposited By: Lee, Prof. Dongheui
Deposited On:17 Dec 2019 13:43
Last Modified:11 Mar 2022 14:22

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