3 research outputs found
A Novel Method for Extrinsic Calibration of Multiple RGB-D Cameras Using Descriptor-Based Patterns
This letter presents a novel method to estimate the relative poses between
RGB-D cameras with minimal overlapping fields of view in a panoramic RGB-D
camera system. This calibration problem is relevant to applications such as
indoor 3D mapping and robot navigation that can benefit from a 360
field of view using RGB-D cameras. The proposed approach relies on
descriptor-based patterns to provide well-matched 2D keypoints in the case of a
minimal overlapping field of view between cameras. Integrating the matched 2D
keypoints with corresponding depth values, a set of 3D matched keypoints are
constructed to calibrate multiple RGB-D cameras. Experiments validated the
accuracy and efficiency of the proposed calibration approach, both superior to
those of existing methods (800 ms vs. 5 seconds; rotation error of 0.56 degrees
vs. 1.6 degrees; and translation error of 1.80 cm vs. 2.5 cm.Comment: 6 pages, 7 figures, under review by IEEE Robotics and Automation
Letters & ICR
Single-pass inline pipeline 3D reconstruction using depth camera array
A novel inline inspection (ILI) approach using depth cameras array (DCA) is introduced to create high-fidelity, dense 3D pipeline models. A new camera calibration method is introduced to register the color and the depth information of the cameras into a unified pipe model. By incorporating the calibration outcomes into a robust camera motion estimation approach, dense and complete 3D pipe surface reconstruction is achieved by using only the inline image data collected by a self-powered ILI rover in a single pass through a straight pipeline. The outcomes of the laboratory experiments demonstrate one-millimeter geometrical accuracy and 0.1-pixel photometric accuracy. In the reconstructed model of a longer pipeline, the proposed method generates the dense 3D surface reconstruction model at the millimeter level accuracy with less than 0.5% distance error. The achieved performance highlights its potential as a useful tool for efficient in-line, non-destructive evaluation of pipeline assets
A Novel Method for Extrinsic Calibration of Multiple RGB-D Cameras Using Descriptor-Based Patterns
This paper presents a novel method to estimate the relative poses between RGB-D cameras with minimal overlapping fields of view. This calibration problem is relevant to applications such as indoor 3D mapping and robot navigation that can benefit from a wider field of view using multiple RGB-D cameras. The proposed approach relies on descriptor-based patterns to provide well-matched 2D keypoints in the case of a minimal overlapping field of view between cameras. Integrating the matched 2D keypoints with corresponding depth values, a set of 3D matched keypoints are constructed to calibrate multiple RGB-D cameras. Experiments validated the accuracy and efficiency of the proposed calibration approach