LidarBoost: Depth superresolution for ToF 3D shape scanning

Depth maps captured with time-of-flight cameras have very low data quality: the image resolution is rather limited and the level of random noise contained in the depth maps is very high. Therefore, such flash lidars cannot be used out of the box for high-quality 3D object scanning. To solve this pro...

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Bibliographic Details
Published in2009 IEEE Conference on Computer Vision and Pattern Recognition pp. 343 - 350
Main Authors Schuon, Sebastian, Theobalt, Christian, Davis, James, Thrun, Sebastian
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2009
Subjects
Cameras
Geometry
Image resolution
Infrared sensors
Laser radar
Layout
Noise level
Noise measurement
Noise shaping
Shape measurement
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Summary:Depth maps captured with time-of-flight cameras have very low data quality: the image resolution is rather limited and the level of random noise contained in the depth maps is very high. Therefore, such flash lidars cannot be used out of the box for high-quality 3D object scanning. To solve this problem, we present LidarBoost, a 3D depth superresolution method that combines several low resolution noisy depth images of a static scene from slightly displaced viewpoints, and merges them into a high-resolution depth image. We have developed an optimization framework that uses a data fidelity term and a geometry prior term that is tailored to the specific characteristics of flash lidars. We demonstrate both visually and quantitatively that LidarBoost produces better results than previous methods from the literature.
ISBN:1424439922
9781424439928
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2009.5206804