GPU Image Resampling for Mobile Object Tracking Control
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Solution Overview
Problem
Modern mobile devices struggle to maintain fast-moving objects in view without requiring significant operator skill, as users must manually adjust the device to keep objects centered in the image frame.
Innovation Solution
A method involving a payload coupled to a carrier that detects deviations of a target from an expected position using an image sensor, generating control signals to adjust the payload's pose, allowing it to automatically track targets by changing its orientation relative to the carrier, thereby maintaining the target within the image frame.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual device adjustment is used to keep objects in view, then the device can track targets, but it requires significant operator skill and cannot effectively track fast-moving objects
Solution Approach 1:
The system enables self-service tracking by automatically detecting target position deviations and generating corresponding control signals to adjust the payload's pose, eliminating the need for manual operator intervention and skill
Solution Approach 2:
The system implements feedback control by continuously monitoring target position in the image frame, comparing it with the expected position, and using the detected deviation to generate corrective control signals that adjust the payload orientation
2Measurement precision
If the payload automatically adjusts its pose to track targets, then tracking precision improves, but the system complexity increases due to control signals and image processing
Solution Approach 1:
The system replaces complex mechanical tracking systems with an integrated electronic control approach, where image processing algorithms and control signal generation work together to achieve precise tracking through software-based deviation detection and automated pose adjustment
3Speed
If the payload changes orientation rapidly to track fast-moving objects, then tracking speed improves, but the stability of the payload-carrying system may deteriorate
Solution Approach 1:
The system implements dynamic tracking by continuously adjusting the payload's pose in real-time based on detected target position deviations, enabling the payload to adapt its orientation dynamically to track fast-moving objects while maintaining system stability through controlled adjustments
Data Source
AI summary
A method for image processing includes a graphics processing unit (GPU) of a mobile device obtaining a first set of image data having a first pixel size and a first color format. The first set of image data is generated by an image sensor of the mobile device. The method further includes the GPU resampling the first set of image data to generate a second set of image data having a second pixel size, and reformatting the second set of image data to generate a third set of image data having a second color format. The third set of image data is used for tracking an object by the mobile device.