CMOS Camera ROI Tracking for High-Speed IR Object Detection
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Solution Overview
Problem
Current object tracking systems using computer vision and IR LEDs are limited by low frame acquisition rates, typically ranging from 30-60 Hz, which hinder the capture of large or quick movements and result in high latency, making them unsuitable for applications requiring smooth tracking of rapid inputs like music synthesis and video game controllers.
Innovation Solution
The implementation of CMOS image sensor technology in camera devices allows for the specification of an active region of interest (ROI), increasing frame acquisition rates by reducing the ROI size, and incorporating an IR LED that is only active when needed, thereby enhancing the tracking of object movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the camera device uses a low frame acquisition rate (30-60 Hz), then the system complexity is reduced, but the ability to capture large or quick movements is limited and latency increases
Solution Approach 1:
The patent divides the image sensing area into a region of interest (ROI) and other areas. By concentrating resources on the ROI, the system achieves higher frame acquisition rates (several hundred Hz) for the tracked object without requiring the entire camera sensor to operate at maximum speed, thus reducing latency while maintaining manageable system complexity.
Solution Approach 2:
The patent applies different quality levels to different regions of the image. The ROI receives high-quality, high-frame-rate processing suitable for tracking rapid movements, while other areas of the image can be processed at lower rates or lower resolution, optimizing overall system performance and reducing latency for the critical tracking function.
2Productivity
If the region of interest size is reduced to increase frame acquisition rate, then the frame rate increases to several hundred Hz, but the detection area is reduced
Solution Approach 1:
The system performs preliminary actions by predicting the future position of the tracked object based on its current motion trajectory. This allows the ROI to be positioned proactively where the object will be, ensuring continuous tracking even as the detection area is reduced to increase frame rate.
Solution Approach 2:
The system uses feedback mechanisms to continuously monitor the object's position and adjust the ROI positioning accordingly. This feedback loop ensures that the reduced detection area remains optimally positioned to capture the tracked object, maintaining effective tracking despite the smaller ROI size.
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
This approach enables higher frame rates, reducing latency and improving the ability to capture quick movements, as demonstrated by achieving frame rates of several hundred Hz, suitable for applications like handwriting recognition and video game controllers, while maintaining object detection accuracy.
Implementation Method 1
the camera device incorporates CMOS image sensor technology and the point light source is an IR LED
Data Source
AI summary
A computer-implemented method for utilizing a camera device to track an object is presented. As part of the method, a region of interest is determined within an overall image sensing area. A point light source is then tracked within the region of interest. In a particular arrangement, the camera device incorporates CMOS image sensor technology and the point light source is an IR LED. Other embodiments pertain to manipulations of the region of interest to accommodate changes to the status of the point light source.