Optical Fiducial Tracking With CMOS Windowing and ROI Readout
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Solution Overview
Problem
Existing optical tracking systems face challenges in achieving high-speed and low-latency data delivery for pose tracking applications, particularly in medical and industrial settings, due to the need for efficient data processing and transmission of large volumes of sensor data.
Innovation Solution
The implementation of CMOS windowing and compression techniques within the optical tracking system, which involves partial sensor data readout, compression, and processing to reduce data volume and latency, utilizing a micro-lens array for simultaneous 2D and 3D image capture, and embedded processing to enhance tracking speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional optical tracking systems process complete sensor data, then measurement precision is maintained, but processing time increases and frame rate decreases
Solution Approach 1:
The patent segments the sensor data processing by dividing the image sensor output into multiple regions of interest (ROIs). Each ROI corresponds to a specific area where fiducials are expected to be located. By processing only these segmented regions rather than the complete image, the system achieves faster processing times and higher frame rates while maintaining tracking precision.
Solution Approach 2:
The patent extracts only the necessary portions of sensor data by reading out partial images from specific regions of interest rather than processing complete images. This extraction of relevant data portions reduces the volume of data requiring processing, directly improving frame rate and reducing processing time latency.
2Measurement precision
If complete sensor data is transmitted for processing, then pose data accuracy is maintained, but data transmission time and latency increase
Solution Approach 1:
The system extracts and transmits only partial image data from regions of interest rather than complete images. This selective extraction reduces data transmission time and latency while maintaining pose data accuracy by ensuring that all regions containing fiducials are captured and transmitted for processing.
Solution Approach 2:
The system performs preliminary identification of regions of interest before data transmission. By pre-determining which areas of the sensor output contain relevant fiducial information, the system prepares the data for efficient transmission and processing, reducing overall latency while maintaining accuracy.
3Measurement precision
If high-resolution complete images are processed, then tracking precision is improved, but processing complexity and computational load increase
Solution Approach 1:
The patent divides the high-resolution image into multiple lower-resolution regions of interest. By segmenting the processing task into smaller regional components rather than processing the complete high-resolution image as a single unit, the system reduces computational complexity and processing load while maintaining tracking precision through focused regional analysis.
Solution Approach 2:
The system applies partial processing by analyzing only specific regions of interest at high resolution rather than processing the entire high-resolution image. This partial action approach reduces computational complexity by limiting processing to necessary areas while maintaining sufficient tracking precision for accurate fiducial detection.
Data Source
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AI summary
A high-speed optical tracking with compression and CMOS windowing for tracking applications that require high-speed and/or low latency when delivering pose (orientation and position) data. The high-speed optical tracking with compression and CMOS windowing generally includes an optical tracking system (10) that sense fiducial (22) and by extension markers (20). The markers can either be integrated on tools (20) handled by an operator (e.g. surgeon) (50) or fixed on the subject to track (e.g. patient) (40). The low-level processing (101, 107, 140) is realized within the tracking system to reduce the overall data to be transferred and considerably reduce the processing efforts. Pose data (127) are finally computed and transferred to a PC/monitor (30,31) or to tablet (60) to be used by an end-user application (130).