| Project/Area Number |
09650471
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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 |
計測・制御工学
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| Research Institution | Osaka University |
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Principal Investigator |
SHIRAI Yoshiaki Faculty of Engneering, Professor, 大学院・工学研究科, 教授 (50206273)
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| Co-Investigator(Kenkyū-buntansha) |
SHIMADA Nobutaka Faculty Of Engneering, Research Associate, 大学院・工学研究科, 助手 (10294034)
MIURA Jun Faculty Of Engneering, Research Associate, 大学院・工学研究科, 助手 (90219585)
KUNO Yoshinori Faculty Of Engneering, Osaka University Associate Professor, 大学院・工学研究科, 助教授 (10252595)
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| Project Period (FY) |
1997 – 1998
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| Project Status |
Completed (Fiscal Year 1998)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 1998: ¥700,000 (Direct Cost: ¥700,000)
Fiscal Year 1997: ¥3,000,000 (Direct Cost: ¥3,000,000)
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| Keywords | human Interface / computer vision / gesture estimation / articulated object / image motion analysis / shape model refinement / probability distribution / constraint knowledge / 単眼視動画像 |
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| Research Abstract |
In order to improve inconvenience of a conservative gesture interface instrument for human-machine interaction such as "wired-glove", we studied the newly non-tactile gesture recognizing method which estimates the 3-Dimensional shape and movement of human body from image sequences captured by TV-cameras without any special wears or marking on a user's body.
First, a hand shape and pose estimation method from monocular silhouette image sequences was studied.Given a roughly shaped model initially, the method estimates rough hand poses.Then it calculates a probability distribution of the model parameters such as finger lengths, palm size and joint angles.Combining observed image features in every image frame and prior knowledge about human hand such as possible ranges of joint angles and relationship between each finger lengths, the distribution is updated and the model shape is modified more precisely.
This estimation algorithm was implemented on a platform constructed from a 3-D highspeed graphics generator and personal computers and experimented for comuter graphics images and real hand images.It was demonstrated the joints angles, finger lengths and palm size can be well-estimated from a monocular images if many views of various shaped hand are obtained.
Since silhouettes contain very limited information about 3-D shape, a method using image motion and depth information was also studied.By precise verification of this method, the shape and pose are wrongly estimated due to approximation errors in probability calculation if accuracy of the image features isnot good.It found other method not using probability is required to resolve the problem.
Next another estimation method which aproximate the possible shape parameter region as a ellipsoid was tested for subsutitution of the probablistic method.It was found this method can correctly estimate even if the image features are errornous.However, it was also found this method is so week in a sudden large errornous input.
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