DocumentCode :
2813996
Title :
Dense scene 3D reconstruction using color based sampling with fusion of image and sparse laser
Author :
Sung, Chang Hun ; Chung, Myung Jin
Author_Institution :
Robot. Program, Korea Adv. Inst. of Sci. & Technol. (KAIST), Daejeon, South Korea
fYear :
2011
fDate :
9-11 Feb. 2011
Firstpage :
1
Lastpage :
6
Abstract :
This paper investigates dense scene 3D reconstruction by fusing camera images and sparse laser data. This paper proposes color based sampling to improve discontinuity between objects, distance accuracy and smoothing of the same object. For robustness to light and camera noise, we apply mean shift filtering to camera image. Distance value is sampled from sparse laser data using color similarity. Kernel based cost function is suggested to estimate distance value from sampled element. We suggest iterative refinement module to find optimal depth data. Color based sampling algorithm is robust to laser noise caused by laser scattering at object edges. Results are presented to demonstrate our proposed algorithm which is robust to image and laser data noise.
Keywords :
edge detection; image colour analysis; image denoising; image fusion; image reconstruction; image sampling; laser noise; object detection; 3D reconstruction; camera image fusing; color based sampling; dense scene reconstruction; image denoising; mean shift filtering; object edge detection; sparse laser; Cameras; Computational modeling; Image color analysis; Laser noise; Reflectivity; Robustness; Variable speed drives; Color based sampling; Dense Scene 3D Reconstruction; fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontiers of Computer Vision (FCV), 2011 17th Korea-Japan Joint Workshop on
Conference_Location :
Ulsan
Print_ISBN :
978-1-61284-677-4
Electronic_ISBN :
978-1-61284-676-7
Type :
conf
DOI :
10.1109/FCV.2011.5739750
Filename :
5739750
Link To Document :
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