TY - GEN
T1 - Image measurement of hand dimensions and model-based human hand posture estimation
AU - Saito, Shunta
AU - Kochi, Makiko
AU - Mochimaru, Masaaki
AU - Aoki, Yoshimitsu
PY - 2010/12/1
Y1 - 2010/12/1
N2 - We have a lot of products designed for use by hand, like a mobile phone, mouse, and camera, etc. These products can be used by many kinds of people whose hands come in various sizes. Designing a handheld product, therefore, it is required to consider the individual difference of user's hands. So there are the high expectations for simulating the interaction between user's hands in various sizes and the product in order to evaluate the product design without prototyping. To achieve it, the technology that generates various Digital Hands automatically from data of hand measurements and finds how a user grasps the product is needed. In this paper, we propose the method that measures 23 lengths and 9 widths included in all fingers automatically from a single image which is got by scanning palm side of a hand using any paper scanner. And we use these resultant measurements for estimating 9 thicknesses and 5 boundary lengths included in fingers or a palm that are perpendicular to the scanned surface. Finally, we try to deform the resultant Digital Hand model into a grasping posture.
AB - We have a lot of products designed for use by hand, like a mobile phone, mouse, and camera, etc. These products can be used by many kinds of people whose hands come in various sizes. Designing a handheld product, therefore, it is required to consider the individual difference of user's hands. So there are the high expectations for simulating the interaction between user's hands in various sizes and the product in order to evaluate the product design without prototyping. To achieve it, the technology that generates various Digital Hands automatically from data of hand measurements and finds how a user grasps the product is needed. In this paper, we propose the method that measures 23 lengths and 9 widths included in all fingers automatically from a single image which is got by scanning palm side of a hand using any paper scanner. And we use these resultant measurements for estimating 9 thicknesses and 5 boundary lengths included in fingers or a palm that are perpendicular to the scanned surface. Finally, we try to deform the resultant Digital Hand model into a grasping posture.
UR - http://www.scopus.com/inward/record.url?scp=78751476633&partnerID=8YFLogxK
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U2 - 10.1109/IECON.2010.5675528
DO - 10.1109/IECON.2010.5675528
M3 - Conference contribution
AN - SCOPUS:78751476633
SN - 9781424452262
T3 - IECON Proceedings (Industrial Electronics Conference)
SP - 1133
EP - 1137
BT - Proceedings - IECON 2010, 36th Annual Conference of the IEEE Industrial Electronics Society
T2 - 36th Annual Conference of the IEEE Industrial Electronics Society, IECON 2010
Y2 - 7 November 2010 through 10 November 2010
ER -