DocumentCode
2292120
Title
Dense 3D reconstruction method using a single pattern for fast moving object
Author
Sagawa, Ryusuke ; Ota, Yuichi ; Yagi, Yasushi ; Furukawa, Ryo ; Asada, Naoki ; Kawasaki, Hiroshi
Author_Institution
Institute of Scientific and Industrial Research, Osaka University, Japan
fYear
2009
fDate
Sept. 29 2009-Oct. 2 2009
Firstpage
1779
Lastpage
1786
Abstract
Dense 3D reconstruction of extremely fast moving objects could contribute to various applications such as body structure analysis and accident avoidance and so on. The actual cases for scanning we assume are, for example, acquiring sequential shape at the moment when an object explodes, or observing fast rotating turbine´s blades. In this paper, we propose such a technique based on a one-shot scanning method that reconstructs 3D shape from a single image where dense and simple pattern are projected onto an object. To realize dense 3D reconstruction from a single image, there are several issues to be solved; e.g. instability derived from using multiple colors, and difficulty on detecting dense pattern because of influence of object color and texture compression. This paper describes the solutions of the issues by combining two methods, that is (1) an efficient line detection technique based on de Bruijn sequence and belief propagation, and (2) an extension of shape from intersections of lines method. As a result, a scanning system that can capture an object in fast motion has been actually developed by using a high-speed camera. In the experiments, the proposed method successfully captured the sequence of dense shapes of an exploding balloon, and a breaking ceramic dish at 300–1000 fps.
Keywords
Accidents; Belief propagation; Blades; Cameras; Ceramics; Image coding; Image reconstruction; Object detection; Reconstruction algorithms; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 2009 IEEE 12th International Conference on
Conference_Location
Kyoto
ISSN
1550-5499
Print_ISBN
978-1-4244-4420-5
Electronic_ISBN
1550-5499
Type
conf
DOI
10.1109/ICCV.2009.5459397
Filename
5459397
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