High Precision Optical Tracking System Based on near Infrared Trinocular Stereo Vision

Area of Science:

• Optics and Photonics
• Computer Vision
• Robotics and Automation

Background:

• Traditional optical tracking systems (OTS) often rely on binocular stereo vision (BSV), which can limit precision and computational efficiency.
• Increasing computational complexity is a challenge with multi-camera systems, hindering real-time applications.

Purpose of the Study:

• To develop a high-precision optical tracking system (OTS) utilizing near-infrared (NIR) trinocular stereo vision (TSV).
• To improve hardware and software components for enhanced tracking accuracy and speed compared to traditional BSV methods.

Main Methods:

• Implementation of a NIR TSV platform with a novel active tool featuring uniform imaging markers and a wide measurement angle (>60°).
• Development of a fast nearest neighbor feature point extraction algorithm (FNNF) to mitigate computational load from additional cameras.
• Application of modified NIR multi-camera calibration and 3D reconstruction algorithms.

Main Results:

• The FNNF algorithm achieved hundreds of times speed improvement over traditional methods for feature point extraction.
• Achieved NIR camera calibration accuracy of 0.02%, marker positioning accuracy of 0.0240 mm, and dynamic tracking accuracy of 0.0938 mm.
• Demonstrated the system's capability for high-precision dynamic tracking.

Conclusions:

• The proposed NIR TSV-based OTS offers significant improvements in accuracy and speed for dynamic tracking.
• The developed FNNF algorithm effectively addresses computational challenges in multi-camera vision systems.
• This advanced OTS is suitable for applications demanding high-precision motion analysis and tracking.