Optical Tracking System Using Strobe Patterns and Kalman Filters
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Solution Overview
Problem
Existing tracking systems face challenges in accurately tracking unpredictable and erratic movements of objects, especially when lighting conditions are poor and objects are far away, and struggle to simultaneously track multiple objects in real-time due to complexity in object recognition and occlusion issues.
Innovation Solution
A system utilizing two cameras and a tracking unit with infrared light sources and inertial measurement units, which combines image tracking and inertial tracking to determine the position and angular orientation of objects using Kalman filters, and employs strobe patterns to distinguish tracking light sources from others, allowing for accurate six-degrees-of-freedom tracking even at distances and in complex environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual imaging systems are used to capture movement, then tracking capability is provided, but processing is resource intensive and tracking response rate slows down
Solution Approach 1:
The patent replaces complex visual image processing with a simpler optical tracking system using light sources and photodetectors. Instead of processing digital images to track movement, the system uses optical signals that can be detected and processed much more quickly, directly addressing the contradiction between reliable tracking and fast response rate.
Solution Approach 2:
The system changes the tracking parameter from image-based position detection to optical signal-based detection. By using light sources with specific characteristics (color, intensity patterns) and photodetectors, the system achieves both reliable tracking and high response rate, as optical signals can be processed much faster than images.
2Length of stationary object
If sensors are positioned further away from the object being tracked, then tracking range is extended, but tracking inaccuracy increases
Solution Approach 1:
The patent applies local quality by using light sources with specific optical characteristics (particular colors, intensity patterns) that create distinct local signatures. This allows the system to maintain high tracking accuracy even at long distances, as each light source has a unique optical signature that can be reliably detected and identified regardless of distance.
Solution Approach 2:
The system uses light sources with specific colors and intensity patterns that create distinguishable optical signatures. By encoding tracking information in optical characteristics rather than relying solely on position detection, the system maintains accuracy at extended ranges.
3Productivity
If multiple objects are tracked simultaneously in real-time, then tracking productivity increases, but complexity in object recognition and occlusion issues increases
Solution Approach 1:
The patent segments the tracking task by assigning unique optical signatures to each light source. Instead of processing complex images to recognize and distinguish multiple objects, the system uses distinct optical identifiers that can be detected independently, greatly simplifying the recognition process while enabling simultaneous multi-object tracking.
Solution Approach 2:
The system introduces optical signals as an intermediary between the objects and the detection system. These optical signals serve as a simplified communication channel that carries identifying information, allowing multiple objects to be distinguished without complex image processing and reducing occlusion-related complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves high-response-rate, accurate tracking of multiple objects in real-time, even at long distances and under varying lighting conditions, by integrating image and inertial data with Kalman filters and strobe patterns, ensuring reliable object identification and positioning.
Implementation Method 1
A system utilizing two cameras and a tracking unit with infrared light sources
Implementation Method 2
combines image tracking and inertial tracking to determine the position and angular orientation of objects
Implementation Method 3
which combines image tracking and inertial tracking to determine the position and angular orientation of objects using Kalman filters
Implementation Method 4
employs strobe patterns to distinguish tracking light sources from others
Data Source
AI summary
Systems and methods are provided for generating calibration information for a media projector. The method includes tracking at least position of a tracking apparatus that can be positioned on a surface. The media projector shines a test spot on the surface, and the test spot corresponds to a known pixel coordinate of the media projector. The system includes a computing device in communication with at least two cameras, wherein each of the cameras are able to capture images of one or more light sources attached to an object. The computing device determines the object's position by comparing images of the light sources and generates an output comprising the real-world position of the object. This real-world position is mapped to the known pixel coordinate of the media projector.