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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

Computer visionArtificial intelligenceComputer scienceLidarPerspective (graphical)Focus (optics)Image fusionRangingImage sensorCalibration

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