TY - GEN
T1 - One-shot scanning method using an uncalibrated projector and camera system
AU - Kawasaki, Hiroshi
AU - Sagawa, Ryusuke
AU - Yagi, Yasushi
AU - Furukawa, Ryo
AU - Asada, Naoki
AU - Sturm, Peter
PY - 2010
Y1 - 2010
N2 - In this paper, we describe a new one-shot scanning technique using a camera and a projector. Generally, a 3D measurement system based on a camera and a projector requires pre-calibration, such as the measurement of the relative position of these devices. If we can eliminate the calibration process, it would greatly improve the convenience of the system. For example, a single capture by a handheld camera of an object illuminated by a hand-held projector would then allow to reconstruct the object shape. To achieve this, we propose a self-calibration technique using a projected grid pattern, computing the relative pose of projector and camera. This is similar to the relative pose or motion problem for two cameras, but in our case correspondences are not explicitly given. The actual algorithm is based on a simple exhaustive search of a finite set of hypotheses, with a cost function based on the epipolar constraint. In the experiments, successful reconstructions with our proposed method using synthetic and read data are presented.
AB - In this paper, we describe a new one-shot scanning technique using a camera and a projector. Generally, a 3D measurement system based on a camera and a projector requires pre-calibration, such as the measurement of the relative position of these devices. If we can eliminate the calibration process, it would greatly improve the convenience of the system. For example, a single capture by a handheld camera of an object illuminated by a hand-held projector would then allow to reconstruct the object shape. To achieve this, we propose a self-calibration technique using a projected grid pattern, computing the relative pose of projector and camera. This is similar to the relative pose or motion problem for two cameras, but in our case correspondences are not explicitly given. The actual algorithm is based on a simple exhaustive search of a finite set of hypotheses, with a cost function based on the epipolar constraint. In the experiments, successful reconstructions with our proposed method using synthetic and read data are presented.
UR - http://www.scopus.com/inward/record.url?scp=77956544169&partnerID=8YFLogxK
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U2 - 10.1109/CVPRW.2010.5544604
DO - 10.1109/CVPRW.2010.5544604
M3 - Conference contribution
AN - SCOPUS:77956544169
SN - 9781424470297
T3 - 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
SP - 104
EP - 111
BT - 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
T2 - 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, CVPRW 2010
Y2 - 13 June 2010 through 18 June 2010
ER -