Statistical Approach to Real-time Estimation of Shape and Pose of Hand and Fingers in Image Sequence
| Project/Area Number |
17500126
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | Ritsumeikan University |
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Principal Investigator |
XU Gang Ritsumeikan University, Department of Media Technology, Professor, 情報理工学部, 教授 (90226374)
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| Co-Investigator(Kenkyū-buntansha) |
NIU Xiaoming Ritsumeikan University, Center for Promotion of the COE, Post-Doctoral Fellow, COE推進機構, ポストドクトラルフェロー (40411243)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 2006: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 2005: ¥1,000,000 (Direct Cost: ¥1,000,000)
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| Keywords | shape of hand and fingers / gesture recognition / independent component analysis / particle filtering / image sequence tracking / ジェスチャー認識 / PCA / 3次元モデル |
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| Research Abstract |
We propose a new approach to hand tracking and 3D motion capture of hand and fingers. This new motion capture system does not require markers be attached to hands.
A hand has many joints. To reduce computational complexity, we propose to reduce dimensionality applying Independent component analysis to the joint angle data collected by a data glove, and as a result the hand shape can be represented by only 5 parameters.
Another problem with hand tracking is that when a hand undergoes free motion, self-occlusion occurs frequently. To solve this problem, we use multiple calibrated cameras. With multiple viewpoints, parts that are not visible to one camera can still be visible to other cameras.
For each image, we try to estimate the 5 parameters representing hand shape and the 6 parameters for hand position and pose (3 for rotation and 3 for translation). These parameters are determined to maximize overlapping between the input image and the back-projected 3D hand model. The optimum is searched using particle filtering, which is robust to local optimum.
The effectiveness of this approach is proved by testing the program to real image sequences with the hand rotating and deforming freely. Experimental results show that the system is robust against occlusion.
However, particle filtering is time-consuming and the system does not work in real-time yet.
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Report
(3 results)
Research Products
(13 results)
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[Book] 最新光三次元計測2006
Author(s)
吉澤徹編著, 分担執筆(徐剛)
Total Pages
152
Publisher
朝倉書店
Description
「研究成果報告書概要(和文)」より
Related Report
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[Book] 写真から作る3次元CG2000
Author(s)
徐剛
Total Pages
145
Publisher
武漢大学出版社(中国語版)
Description
「研究成果報告書概要(和文)」より
Related Report
