3D Point Cloud Reconstruction via Infrared Depth Fusion
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Solution Overview
Problem
Existing three-dimensional reconstruction technologies face limitations in generating complete and high-quality three-dimensional point cloud images when the object is blocked or moves beyond the viewing angle range of the device, leading to restricted motion flexibility during real-time tracking.
Innovation Solution
A method and apparatus that utilize an infrared camera and a marker measurement device to detect three-dimensional shape and marker coordinates, respectively, and convert them into a three-dimensional point cloud image, allowing for real-time tracking and reconstruction even when the object is blocked or moves beyond the initial viewing angle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a special device (RGBD camera or laser scanner) is used to acquire three-dimensional information, then the quality and completeness of the three-dimensional point cloud image within the given angular distance range is improved, but the motion flexibility of the three-dimensional object is restricted when the object moves beyond the viewing range or is blocked
Solution Approach 1:
The system segments the three-dimensional reconstruction task into two independent parts: a color camera captures color information within its viewing range, while an infrared camera captures depth information including occluded regions. This segmentation allows each sensor to operate independently in its optimal range, resolving the contradiction between image quality and motion flexibility.
Solution Approach 2:
The infrared camera acts as an intermediary that captures depth information in regions where the color camera cannot observe (occluded or distant areas). By fusing the color data from the color camera with depth data from the infrared camera, the system maintains complete three-dimensional reconstruction even when the object moves beyond the color camera's viewing range.
2Reliability
If the motion of the three-dimensional object is limited to a given angular distance range to ensure complete information acquisition, then the completeness of the three-dimensional point cloud image is improved, but the motion flexibility during real-time tracking is reduced
Solution Approach 1:
The system dynamically adapts to object motion by using the infrared camera's ability to capture depth information beyond the color camera's viewing angle. As the object moves or is occluded, the infrared camera continuously provides depth data, allowing the system to maintain reliable three-dimensional reconstruction without restricting object motion.
Solution Approach 2:
The system changes the operational parameters by switching from relying solely on the color camera (limited viewing angle) to fusing infrared depth data (extended viewing range). This parameter change enables the system to maintain image completeness while allowing greater motion flexibility during real-time tracking.
3Measurement precision
If a color camera is used to capture three-dimensional information, then the color accuracy of the point cloud image is improved, but the acquisition viewing angle range is limited causing incomplete reconstruction when the object is blocked
Solution Approach 1:
The system merges the color camera (providing accurate color information within its viewing range) with the infrared camera (providing depth information in occluded and distant regions). This combination allows the final point cloud to have both accurate colors where visible and complete geometric information in occluded areas, resolving the contradiction between color accuracy and viewing angle range.
Solution Approach 2:
The system transitions from a two-dimensional color image capture (color camera with limited viewing angle) to a three-dimensional depth map capture (infrared camera with extended viewing range). By fusing these different dimensional data, the system achieves complete three-dimensional reconstruction with color information without being constrained by the color camera's viewing angle.
Data Source
AI summary
A method and an apparatus for generating a three-dimensional point cloud image, a computer device and a storage medium. The method comprises: detecting three-dimensional shape coordinates of a three-dimensional object in an infrared camera coordinate system; detecting three-dimensional marker coordinates of the marker set in a marker measurement coordinate system at the same time; obtaining, according to a pre-stored first conversion relationship and a second conversion relationship parameter, three-dimensional color coordinates in the infrared camera coordinate system on the basis of the three-dimensional marker coordinates in the marker measurement coordinate system; and generating a three-dimensional point cloud image of the three-dimensional object in the infrared camera coordinate system by combining the three-dimensional shape coordinates and the three-dimensional color coordinates of the three-dimensional object in the infrared camera coordinate system.