By Topic

Dense scene 3D reconstruction using color based sampling with fusion of image and sparse laser

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chang Hun Sung ; Robot. Program, Korea Adv. Inst. of Sci. & Technol. (KAIST), Daejeon, South Korea ; Myung Jin Chung

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.

Published in:

Frontiers of Computer Vision (FCV), 2011 17th Korea-Japan Joint Workshop on

Date of Conference:

9-11 Feb. 2011