Perspective Crop Based Egocentric Hand Pose Estimation via Fisheye Stereo Vision
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In this paper, we propose a method to improve the performance of hand pose estimation from egocentric view. To accurately capture hands moving within a wide range in daily activities, we mounted a fisheye stereo camera on a head mounted display to obtain wide-angle images from egocentric view. Our proposed two-stage method addresses the camera distortion introduced by this setup. The 2D hand keypoints estimated by stage-1 HandNet are converted into 3D hand keypoints through triangulation for perspective cropping. Stage-2 HandNet then predicts the final 2D hand keypoints from the undistorted hand crop image. To train stage-1 HandNet for perspective cropping, we built FisheyeEgoHAND dataset which consists of three categories of scenarios (separate hand, hand-hand, and hand-object) that reflect various hand interactions in an egocentric view. Through experiments, we demonstrated that two-stage 2D hand pose estimation outperforms one-stage approach without perspective cropping.
Description
CCS Concepts: Computing methodologies → Computer vision; Vision for robotics
@inproceedings{10.2312:egp.20251016,
booktitle = {Eurographics 2025 - Posters},
editor = {Günther, Tobias and Montazeri, Zahra},
title = {{Perspective Crop Based Egocentric Hand Pose Estimation via Fisheye Stereo Vision}},
author = {Hur, Hyejin and Baek, Seongmin and Gil, Younhee and Kim, Sangpil},
year = {2025},
publisher = {The Eurographics Association},
ISSN = {1017-4656},
ISBN = {978-3-03868-269-1},
DOI = {10.2312/egp.20251016}
}