A hand pose tracking benchmark from stereo matching

Jiawei Zhang; Jianbo Jiao; Mingliang Chen; Liangqiong Qu; Xiaobin Xu; Qingxiong Yang

doi:10.1109/ICIP.2017.8296428

A hand pose tracking benchmark from stereo matching

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

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

93 Citations (Scopus)

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.

Original language	English
Title of host publication	2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
Publisher	IEEE
Pages	982-986
ISBN (Electronic)	978-1-5090-2175-8
DOIs	https://doi.org/10.1109/ICIP.2017.8296428
Publication status	Published - Sept 2017
Event	24th IEEE International Conference on Image Processing (ICIP 2017) - China National Convention Center, Beijing, China Duration: 17 Sept 2017 → 20 Sept 2017 http://2017.ieeeicip.org/ https://ieeexplore.ieee.org/xpl/conhome/8267582/proceeding

Conference

Conference	24th IEEE International Conference on Image Processing (ICIP 2017)
Abbreviated title	ICIP
Place	China
City	Beijing
Period	17/09/17 → 20/09/17
Internet address	http://2017.ieeeicip.org/ https://ieeexplore.ieee.org/xpl/conhome/8267582/proceeding

Research Keywords

Stereo matching and hand pose tracking

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10.1109/ICIP.2017.8296428

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@inproceedings{f9ae6c735463475ba26c10d791566d16,

title = "A hand pose tracking benchmark from stereo matching",

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.",

keywords = "Stereo matching and hand pose tracking",

author = "Jiawei Zhang and Jianbo Jiao and Mingliang Chen and Liangqiong Qu and Xiaobin Xu and Qingxiong Yang",

year = "2017",

month = sep,

doi = "10.1109/ICIP.2017.8296428",

language = "English",

pages = "982--986",

booktitle = "2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings",

publisher = "IEEE",

address = "United States",

note = "24th IEEE International Conference on Image Processing (ICIP 2017), ICIP ; Conference date: 17-09-2017 Through 20-09-2017",

url = "http://2017.ieeeicip.org/, https://ieeexplore.ieee.org/xpl/conhome/8267582/proceeding",

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TY - GEN

T1 - A hand pose tracking benchmark from stereo matching

AU - Zhang, Jiawei

AU - Jiao, Jianbo

AU - Chen, Mingliang

AU - Qu, Liangqiong

AU - Xu, Xiaobin

AU - Yang, Qingxiong

PY - 2017/9

Y1 - 2017/9

N2 - 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.

AB - 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.

KW - Stereo matching and hand pose tracking

UR - https://www.scopus.com/pages/publications/85045308936

UR - https://www.scopus.com/pages/publications/85045308936#tab=impact

U2 - 10.1109/ICIP.2017.8296428

DO - 10.1109/ICIP.2017.8296428

M3 - RGC 32 - Refereed conference paper (with host publication)

SP - 982

EP - 986

BT - 2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings

PB - IEEE

T2 - 24th IEEE International Conference on Image Processing (ICIP 2017)

Y2 - 17 September 2017 through 20 September 2017

ER -

A hand pose tracking benchmark from stereo matching

Abstract

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Research Keywords

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Interactive Object Extraction with Object Proposals and Background Subtraction

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A hand pose tracking benchmark from stereo matching

Abstract

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Research Keywords

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Student theses

Interactive Object Extraction with Object Proposals and Background Subtraction

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