Orientation-Aware Template Matching for Low-Cost Image Tracking
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Solution Overview
Problem
Existing image processing systems face increased processing costs and time due to the need for rotation processing of input images when handling variations in image capturing orientation, particularly in low-cost systems.
Innovation Solution
An image processing apparatus and method that sets filter coefficients based on orientation information to generate feature maps, registers template features, and performs correlation calculations efficiently, allowing detection of target objects regardless of image capturing orientation without requiring extensive rotation of input images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If rotation processing of the input image is executed to handle variations in image capturing orientation, then the tracking processing can be continued regardless of orientation, but the processing time increases and a large buffer memory becomes necessary
Solution Approach 1:
Instead of rotating the input image to match a fixed template orientation, the patent inverts the approach by rotating the template feature to match the orientation detected in the current input image. This is achieved by detecting the orientation of the target object in the input image and rotating the stored template feature accordingly before performing correlation calculation, thereby eliminating the need for time-consuming input image rotation while maintaining tracking continuity across different orientations.
Solution Approach 2:
The patent performs preliminary orientation detection on the target object in the input image before the correlation calculation step. By detecting the orientation advance and pre-rotating the template feature to match this detected orientation, the system prepares the template in advance for the correlation calculation, avoiding the need for time-consuming rotation processing during the main tracking loop and reducing overall processing time.
2Adaptability or versatility
If rotation processing of the input image is executed to handle variations in image capturing orientation, then the tracking processing can be continued regardless of orientation, but a large buffer memory for processing becomes necessary
Solution Approach 1:
Instead of rotating the input image which would require large buffer memory to store the rotated image data, the patent inverts the approach by rotating only the template feature (a much smaller data structure) to match the input image orientation. This eliminates the need for large buffer memory allocation while still enabling tracking continuity across different orientations.
Solution Approach 2:
The patent extracts and rotates only the essential template feature data rather than processing the entire input image. By taking out just the template feature (a small matrix of feature values) and rotating it to match the detected orientation, the system avoids the memory-intensive operation of rotating and storing the full input image, thereby reducing buffer memory requirements significantly.
3Loss of energy
If filter coefficients are set based on orientation information and correlation calculation is optimized, then processing costs are reduced, but the system must handle varying orientations efficiently
Solution Approach 1:
The patent changes the orientation parameter of the template feature to match the detected orientation in the input image. By adjusting the orientation parameter and rotating the template feature accordingly before correlation calculation, the system efficiently adapts to varying orientations while maintaining optimized processing costs, as the rotation is performed on small template data rather than large image data.
Solution Approach 2:
The patent makes the template feature dynamic by rotating it according to the detected orientation of the target object in the input image. This dynamic adjustment allows the template to adapt to different orientations in real-time during tracking, enabling the system to handle varying orientations efficiently while maintaining low processing costs through optimized correlation calculation on the rotated template.
Data Source
AI summary
An apparatus sets coefficients in a first array based on first information indicating an image capturing orientation of a first image, generates a first map by applying the coefficients to the first image, acquires a template feature corresponding to an object based on the first map, registers the template feature in an array based on the first information, sets coefficients in a second array based on second information indicating an image capturing orientation of a second image, generates a second map by applying the coefficients set in the second array to the second image, sets the template feature in a feature array based on the second information, performs a correlation calculation between the template feature set in the feature array and the second map, and detects the object from the second image based on a result of the correlation calculation.