Dense surface reconstruction based on the fusion of monocular vision and three-dimensional flash light detection and ranging

Gangtao Hao; Xiaoping Du; Ji-Guang Zhao; Hang Chen; Jianjun Song; Yishuo Song

doi:10.1117/1.OE.54.7.073113

27 July 2015 Dense surface reconstruction based on the fusion of monocular vision and three-dimensional flash light detection and ranging

Gangtao Hao, Xiaoping Du, Ji-Guang Zhao, Hang Chen, Jianjun Song, Yishuo Song

Author Affiliations +

Optical Engineering, Vol. 54, Issue 7, 073113 (July 2015). https://doi.org/10.1117/1.OE.54.7.073113

Abstract

A dense surface reconstruction approach based on the fusion of monocular vision and three-dimensional (3-D) flash light detection and ranging (LIDAR) is proposed. The texture and geometry information can be obtained simultaneously and quickly for stationary or moving targets with the proposed method. Primarily, our 2-D/3-D fusion imaging system including cameras calibration and an intensity-range image registration algorithm is designed. Subsequently, the adaptive block intensity-range Markov random field (MRF) with optimizing weights is presented to improve the sparse range data from 3-D flash LIDAR. Then the energy function is minimized quickly by conjugate gradient algorithm for each neighborhood system instead of the whole MRF. Finally, the experiments with standard depth datasets and real 2-D/3-D images demonstrate the validity and capability of the proposed scheme.

Citation Download Citation

Gangtao Hao, Xiaoping Du, Ji-Guang Zhao, Hang Chen, Jianjun Song, and Yishuo Song "Dense surface reconstruction based on the fusion of monocular vision and three-dimensional flash light detection and ranging," Optical Engineering 54(7), 073113 (27 July 2015). https://doi.org/10.1117/1.OE.54.7.073113

Published: 27 July 2015

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available