A hand pose tracking benchmark from stereo matching
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | 2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers, Inc. |
Pages | 982-986 |
ISBN (electronic) | 978-1-5090-2175-8 |
Publication status | Published - Sept 2017 |
Conference
Title | 24th IEEE International Conference on Image Processing (ICIP 2017) |
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Location | China National Convention Center |
Place | China |
City | Beijing |
Period | 17 - 20 September 2017 |
Link(s)
Abstract
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.
Research Area(s)
- Stereo matching and hand pose tracking
Citation Format(s)
A hand pose tracking benchmark from stereo matching. / Zhang, Jiawei; Jiao, Jianbo; Chen, Mingliang et al.
2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings. Institute of Electrical and Electronics Engineers, Inc., 2017. p. 982-986.
2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings. Institute of Electrical and Electronics Engineers, Inc., 2017. p. 982-986.
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review