Image Target Tracking Using Low-Resolution Region Preselection
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Solution Overview
Problem
Existing image processing technologies for tracking objects require complex apparatus configurations and high processing loads, making them inefficient for accurate target specification.
Innovation Solution
A processing apparatus that converts high-resolution images into lower-resolution images, allowing for efficient target specification and tracking by reducing processing load, while also enabling gesture recognition and control of mobile objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing is performed on high-resolution images to accurately specify targets, then measurement precision is improved, but processing load increases
Solution Approach 1:
The image processing is segmented into two stages: first processing low-resolution images to obtain target region candidates, then processing only those specific regions in high-resolution images. This division reduces the overall processing load while maintaining accurate target specification.
Solution Approach 2:
Different resolution qualities are applied to different regions of the image. Low-resolution processing is applied to the entire image for initial target region detection, while high-resolution processing is applied only to identified target regions for final accurate specification.
2Measurement precision
If complex image processing algorithms are used to track objects accurately, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The tracking system is segmented into a coarse tracking component that operates on low-resolution images and a fine tracking component that operates on high-resolution images. This segmentation simplifies each individual component while achieving accurate overall tracking.
Solution Approach 2:
Low-resolution images serve as an intermediary to guide the processing of high-resolution images. The target regions identified in low-resolution images act as intermediaries that direct where detailed high-resolution analysis should be focused.
3Measurement precision
If high-resolution images are processed in real-time for gesture recognition, then measurement precision is improved, but loss of time increases
Solution Approach 1:
High-resolution processing is applied locally only to regions containing gestures rather than the entire image. This maintains accurate gesture recognition while reducing the time required for processing.
Solution Approach 2:
Target regions are preliminarily identified using low-resolution images before performing detailed gesture recognition on high-resolution images. This preliminary action reduces the amount of data that requires time-consuming high-resolution processing.
Data Source
AI summary
A processing apparatus converts a first image into a second image with a lower resolution than a resolution of the first image, specifies a target region including a predetermined objective target in the second image on the basis of the second image, and specifies a target region including the objective target in the first image on the basis of the specified target region in the second image.