DocumentCode
2860733
Title
Sensing Deforming and Moving Objects with Commercial Off the Shelf Hardware
Author
Fong, Philip ; Buron, Florian
Author_Institution
Stanford University
fYear
2005
fDate
25-25 June 2005
Firstpage
101
Lastpage
101
Abstract
In many application areas, there exists a crucial need for capturing 3D videos of fast moving and/or deforming objects. A 3D video is a sequence of 3D representations at high time and space resolution. Although many 3D sensing techniques are available, most cannot deal with dynamic scenes (e.g. laser scanning), can only deal with textured surfaces (e.g. stereo vision) and/or require expensive specialized hardware. This paper presents a technique to compute high-resolution range maps from single images of moving and deformable objects. A camera observes the deformation of a projected light pattern that combines a set of parallel colored stripes and a perpendicular set of sinusoidal intensity stripes. While the colored stripes allow recovering absolute depths at coarse resolution, the sinusoidal intensity stripes give dense relative depths. This twofold pattern makes it possible to extract a high-resolution range map from each image captured by the camera. This approach is based on sound mathematical principles, but its implementation requires giving great care to a number of low-level details. In particular, the sensor has been implemented using commercial off the shelf hardware, which distorts sensed and transmitted signals in many ways. A novel method was developed to characterize and compensate for distortions due to chromatic aberrations. The sensor has been tested on several moving and deforming objects.
Keywords
Acoustic sensors; Cameras; Distortion; Hardware; Layout; Sensor phenomena and characterization; Stereo vision; Surface emitting lasers; Surface texture; Videos;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition - Workshops, 2005. CVPR Workshops. IEEE Computer Society Conference on
Conference_Location
San Diego, CA, USA
ISSN
1063-6919
Print_ISBN
0-7695-2372-2
Type
conf
DOI
10.1109/CVPR.2005.524
Filename
1565411
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