Share Email Print
cover

Proceedings Paper

Fast 3D foot modeling based on simulated laser speckle projection stereo and silhouette
Author(s): Yunpeng Li; Fugen Zhang; Baozhen Ge; Qingguo Tian
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

3D foot digital models have great potential for application in ergonomics design and online virtual shoes try-on. Traditional techniques usually take 10 seconds to several minutes to acquire dense data, which is a critical limitation to large scale data collection. To enhance data collection efficiency, a novel approach which combines simulated laser speckle projection stereo with 3D silhouette is proposed. Laser speckle has more statistical advantages so that it can deal with lacking of texture of human skin and make stereo matching easier. With dark field lighting that strengthen foot contour, 3D silhouette can remove border noise caused by our active stereo reconstruction. Besides, all light sources in our work are infrared to avoid ambient light inference. In our design, five active stereo rigs are installed around 4π solid angle centered at the foot position to capture whole foot’s surface mesh data. Composed of a pair of stereo IP-cameras with visible cut filters, an infrared simulated laser speckle mini film projector and a cluster of infrared LEDs surrounding camera lens, each active stereo rig takes charge of obtaining 3D information of corresponding foot part. The five rigs are controlled by an MCU controller to successively capture one pair of speckle pattern images for stereo reconstruction and one pair of edge enhanced dark field lighting images for silhouette. The system design resolution is less than 0.3 mm per pixel. Data capture could be performed in less than 1 second for each foot and more than 500 thousand valid points are acquired as dense point cloud model. Finally, foot mesh model is generated using Poisson reconstruction algorithm.

Paper Details

Date Published: 2 November 2018
PDF: 10 pages
Proc. SPIE 10819, Optical Metrology and Inspection for Industrial Applications V, 108190H (2 November 2018); doi: 10.1117/12.2502429
Show Author Affiliations
Yunpeng Li, Tianjin Univ. (China)
Fugen Zhang, Jiangsu Liangtao Data Technology Co., Ltd. (China)
Baozhen Ge, Tianjin Univ. (China)
Qingguo Tian, Tianjin Univ. (China)


Published in SPIE Proceedings Vol. 10819:
Optical Metrology and Inspection for Industrial Applications V
Sen Han; Toru Yoshizawa; Song Zhang, Editor(s)

© SPIE. Terms of Use
Back to Top