LiDAR-ToF-Binocular depth fusion using gradient priors
Xiaoming Zhao, Weihai Chen, Ziyang Liu, Xinzhi Ma, Lingkun Kong, Xingming Wu, Haosong Yue, Yan Xing
- Year
- 2020
- Citations
- 6
Abstract
Most robotic systems face a complex environment in which a single vision sensor cannot fully sense surroundings. In this paper, we focus on how to combining the depth image of traditional binocular camera, novel ToF (time-of-flight) camera and emerging 16-line LiDAR (light detection and ranging), to accurately obtain a dense depth image. In order to unify the depth image to the same perspective of different sensors, we employ a simple method for extrinsic parameter calibration. Based on the unified depth image, a fast and accurate fusion algorithm is developed. Our experiments illustrate that the proposed method can greatly improve the depth density and accuracy, while keeping a fast running speed.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991