Tag Tracking via Movement Prediction and Segmented Template Matching
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Solution Overview
Problem
Existing tag tracking systems face challenges in maintaining high accuracy and reducing costs when increasing spatial resolution or performing template matching, especially when dealing with moving tags that have longer lighting-off times and higher movement speeds.
Innovation Solution
An information processing apparatus that acquires and processes images of blinking tags, considering the distance between tag positions in successive images to determine if they are the same tag, and specifies the pattern based on these images, reducing the need for high-speed imaging and complex template matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If template matching is performed to achieve high-accuracy tag tracking, then measurement precision is improved, but calculation amount increases
Solution Approach 1:
The patent segments the tag tracking process into two distinct phases: (1) rough positioning using movement range prediction to identify candidate regions, and (2) precise positioning using template matching only within those limited candidate regions. This segmentation reduces the overall calculation amount while maintaining tracking accuracy by avoiding exhaustive template matching across the entire image.
Solution Approach 2:
The system performs preliminary action by predicting the movement range of tags between frames and pre-defining candidate regions before template matching is executed. This preliminary positioning step narrows down the search space, allowing template matching to focus computational resources only on relevant areas, thus reducing total calculation amount while preserving measurement precision.
2Measurement precision
If spatial resolution is increased to improve tracking accuracy, then measurement precision is improved, but monetary cost increases
Solution Approach 1:
The patent applies segmentation by dividing the image processing into coarse positioning (using low-resolution movement prediction) and fine positioning (using template matching on candidate regions). This allows the system to achieve high tracking accuracy without requiring the entire system to operate at high spatial resolution, thereby reducing hardware costs while maintaining measurement precision.
Solution Approach 2:
The system performs partial action by applying high-resolution template matching only to specific candidate regions rather than the entire image. This selective approach achieves the necessary measurement precision for accurate tag tracking while reducing the overall computational burden and associated hardware costs, making the system more economically viable.
3Measurement precision
If imaging frequency is increased to track fast-moving tags, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The system performs preliminary action by predicting tag movement ranges based on previous positions and velocities. This prediction allows the system to determine candidate regions in advance, reducing the need for frequent full-image captures. The imaging frequency can be reduced while maintaining measurement precision because the prediction guides where to look next, avoiding unnecessary high-energy imaging operations.
Solution Approach 2:
The patent segments the imaging process into predictive positioning (low energy) and verification imaging (higher energy) only when needed. By using movement prediction to identify candidate regions, the system reduces overall imaging frequency while maintaining tracking accuracy, thereby reducing energy consumption associated with high-frequency imaging.
Data Source
AI summary
An information processing apparatus includes a processor configured to acquire, among a plurality of images obtained by periodically capturing one or more lighting devices that repeat blinking according to a determined pattern, a first image and a second image in which a lighted lighting device is captured and in response to a distance from a position of the device indicated by the first image to a position of the device indicated by the second image being within a range corresponding to a period from a time of capturing the first image to a time of capturing the second image, regard the lighting device indicated by the first image and the lighting device indicated by the second image are the same, and specify the pattern of the lighting device that has been regarded the same.