Optical Marker Tracking for Fast, Reliable Object Positioning
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Solution Overview
Problem
Current object tracking systems using optical markers face challenges in accurately detecting and classifying optical markers in diverse environments with minimal processing time and high reliability, particularly in scenarios with complex backgrounds and varying lighting conditions.
Innovation Solution
The system employs an optical marker dictionary with distinct markers affixed to objects, using computer vision and machine learning algorithms to detect and classify optical markers in image data from cameras, determining camera position and relative marker positions to project accurate position information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If computer vision algorithms are applied to detect optical markers in complex environments with varying lighting conditions, then tracking reliability is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-processing images to enhance optical markers before detection. The system performs image normalization, contrast enhancement, and noise filtering in advance to prepare the data for faster and more reliable marker detection, thereby improving tracking reliability without significantly increasing real-time processing time
Solution Approach 2:
The patent applies segmentation by dividing the image processing task into distinct stages: pre-processing, marker detection, position calculation, and tracking updates. This segmentation allows each stage to be optimized independently, with parallel processing capabilities that reduce overall processing time while maintaining high tracking reliability through specialized algorithms for each segment
2Measurement precision
If optical markers are made more distinct to improve detection accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies local quality by designing optical markers with specific local characteristics optimized for detection. Each marker contains unique local features such as specific color patterns, shapes, and spatial arrangements that enhance detectability and measurement precision without requiring complex global marker designs or multiple marker types
Solution Approach 2:
The patent applies color changes by utilizing multiple color channels and color variations in optical markers. The system detects markers based on their color properties and uses color information to distinguish markers from complex backgrounds, improving detection accuracy while maintaining relatively simple marker designs that can be implemented with standard colored materials
Data Source
AI summary
Embodiments include system and processes for tracking objects using a camera. An optical marker dictionary including one or more optical markers is generated, the optical markers being optically distinct indicators. An optical marker within the optical marker dictionary is associated with and affixed to an object. A processor is in communication with the camera, receiving image data from the camera and applying computer vision to the image data in order to detect the presence of one or more optical markers within the optical marker dictionary within the image data. The processor determines camera position information and applies computer vision to the image data in order to determine relative position information for the detected optical markers and projects a position from the camera to a detected optical marker.