A hand pose tracking benchmark from stereo matching

Jiawei Zhang, Jianbo Jiao, Mingliang Chen, Liangqiong Qu, XU Xiaobin, Qingxiong Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In this paper we establish a long-term 3D hand pose tracking benchmark1. It contains 18,000 stereo image pairs as well as the ground-truth 3D positions of palm and finger joints from different scenarios. Meanwhile, to accurately segment hand from stereo images, we propose a novel stereo-based hand segmentation and depth estimation algorithm specially tailored for hand tracking here. The experiments indicate the effectiveness of the proposed algorithm by demonstrating that its tracking performance is comparable to the use of an active depth sensor under various of challenging scenarios.
Original languageEnglish
Title of host publication2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
Publication statusPublished - Sept 2017


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