TY - GEN
T1 - Single color one-shot scan using topology information
AU - Kawasaki, Hiroshi
AU - Masuyama, Hitoshi
AU - Sagawa, Ryusuke
AU - Furukawa, Ryo
PY - 2012/1/1
Y1 - 2012/1/1
N2 - In this paper, we propose a new technique to achieve one-shot scan using single color and static pattern projector; such a method is ideal for acquisition of a moving object. Since a projector-camera systems generally have uncertainties on retrieving correspondences between the captured image and the projected pattern, many solutions have been proposed. Especially for one-shot scan, which means that only a single image is used for reconstruction, positional information of a pixel on the projected pattern should be encoded by spatial and/or color information. Although color information is frequently used for encoding, it is severely affected by texture and material of the object. In this paper, we propose a technique to solve the problem by using topological information instead of colors. Our technique successfully realizes one-shot scan with monochrome pattern.
AB - In this paper, we propose a new technique to achieve one-shot scan using single color and static pattern projector; such a method is ideal for acquisition of a moving object. Since a projector-camera systems generally have uncertainties on retrieving correspondences between the captured image and the projected pattern, many solutions have been proposed. Especially for one-shot scan, which means that only a single image is used for reconstruction, positional information of a pixel on the projected pattern should be encoded by spatial and/or color information. Although color information is frequently used for encoding, it is severely affected by texture and material of the object. In this paper, we propose a technique to solve the problem by using topological information instead of colors. Our technique successfully realizes one-shot scan with monochrome pattern.
UR - http://www.scopus.com/inward/record.url?scp=84867696017&partnerID=8YFLogxK
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U2 - 10.1007/978-3-642-33885-4_49
DO - 10.1007/978-3-642-33885-4_49
M3 - Conference contribution
AN - SCOPUS:84867696017
SN - 9783642338847
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 486
EP - 495
BT - Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
PB - Springer Verlag
T2 - 12th European Conference on Computer Vision, ECCV 2012
Y2 - 7 October 2012 through 13 October 2012
ER -