Monocular Vision Tracking Using Wireless Tracker and Calibration Board
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Solution Overview
Problem
Current monocular vision tracking technologies are costly and not suitable for ordinary pre-research or preliminary evaluations, requiring expensive hardware and being difficult to implement for general developers, with camera pose estimation accuracy reduced due to variable camera focal lengths on mobile platforms.
Innovation Solution
A method using a wireless tracker and a camera, such as a mobile phone with a VR head-mounted tracker, to acquire and convert camera poses through calibration board images, normalizing imaging model parameters and performing hand-eye calibration to synchronize camera and tracker poses, allowing for cost-effective construction of a monocular vision tracking database suitable for various scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive devices such as 3D laser tracker, Vicon, or stereo camera are used to obtain camera true pose, then measurement precision is improved, but device cost increases significantly
Solution Approach 1:
The patent uses a wireless tracker to capture motion information and a camera to capture calibration board images, creating a simplified copy of the expensive tracking system. The wireless tracker and camera combination reproduces the essential tracking function at a fraction of the cost of 3D laser trackers or Vicon systems, while maintaining sufficient accuracy for monocular vision tracking research
Solution Approach 2:
The calibration board serves as an intermediary object that bridges the wireless tracker and camera. By capturing images of the calibration board at multiple positions and orientations, the system establishes a relationship between the wireless tracker's coordinate system and the camera's coordinate system, enabling pose conversion without requiring direct integration of expensive hardware
2Measurement precision
If hardware time-synchronized acquisition method is used, then measurement precision is improved, but ease of operation deteriorates due to difficulty in implementation for general developers
Solution Approach 1:
The patent replaces complex hardware time-synchronization mechanisms with a software-based post-processing approach. Instead of requiring hardware-level synchronization that is difficult to implement, the system uses recorded calibration board images and wireless tracker data to computationally establish the relationship between coordinate systems, making the synchronization process accessible to general developers through software algorithms rather than complex hardware configuration
3Ease of operation
If camera imaging model is assumed unchanged, then ease of operation is improved, but measurement precision deteriorates due to variable focal length on mobile platforms
Solution Approach 1:
The patent incorporates feedback by capturing calibration board images at multiple positions and orientations, then using these images to compute and update the camera's intrinsic parameters and pose. This feedback loop allows the system to adapt to variable focal lengths and imaging model changes by continuously recalibrating based on actual captured images, maintaining accuracy despite mobile platform hardware variations
Data Source
AI summary
A monocular vision tracking method, apparatus, and a non-volatile computer-readable storage medium are provided. The method includes: acquiring a first camera pose by using a wireless tracker; capturing calibration board images by using a camera, and selecting a set of images from the captured calibration board images according to image sharpness and camera pose difference; calculating a second camera pose in the camera calibration algorithm according to the selected set of images; obtaining a conversion parameter between the first camera pose and the second camera pose; and converting a first capturing pose into a second capturing pose by means of the conversion parameter when a scenario is captured, wherein the first capturing pose is acquired by the wireless tracker and the second capturing pose corresponds to a pose of the camera.