Trajectory Analysis Using Bidirectional Tracking Correlation
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Solution Overview
Problem
Existing moving-object tracking technologies face challenges in maintaining high accuracy, especially when objects move quickly or change appearance significantly, leading to reduced tracking accuracy and inability to output significant trajectory information when accuracy falls below a certain level.
Innovation Solution
A trajectory analyzing apparatus and method that calculates correlation between forward and backward trajectories and outputs integrated trajectory information with reliability indicators, allowing for high significance output even at low tracking accuracy levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a moving-object tracking algorithm is used to track a moving object along the forward direction of the time axis, then the tracking accuracy is high when the object is close to the start point, but the tracking accuracy decreases as the object moves away from the start point due to error accumulation
Solution Approach 1:
The patent divides the tracking process into multiple segments by performing tracking from both forward and backward directions, then integrating the results. This segmentation approach prevents error accumulation in single-direction tracking by creating multiple independent tracking paths that can be cross-validated and merged.
Solution Approach 2:
The patent applies backward tracking from the end of the trajectory in addition to forward tracking from the beginning. By inverting the tracking direction and integrating both results, the system compensates for error accumulation in long trajectories and maintains high accuracy throughout the entire path.
2Measurement precision
If the moving-object tracking algorithm is changed to another algorithm, then the tracking accuracy may improve for some cases, but the tracking accuracy still cannot reach the predetermined level for fast-moving or appearance-changing objects
Solution Approach 1:
The patent creates a universal tracking system that integrates results from multiple different tracking algorithms (forward and backward tracking). This multi-functional approach allows the system to handle diverse object types including fast-moving objects and objects with appearance changes, achieving high accuracy across various scenarios without requiring a single specialized algorithm.
Solution Approach 2:
The patent combines multiple tracking algorithm results into a composite trajectory solution. By merging forward and backward tracking results, the system creates a more robust and accurate trajectory estimation that leverages the strengths of different algorithms while compensating for their individual weaknesses.
3Measurement precision
If bidirectional tracking is performed with multiple algorithms, then the tracking accuracy improves, but the device complexity increases due to multiple tracking processes
Solution Approach 1:
The patent merges forward and backward tracking results into a single integrated trajectory. By combining the results from both directions using correlation analysis and reliability assessment, the system achieves high tracking accuracy while managing complexity through a unified integration framework rather than maintaining separate independent tracking systems.
Solution Approach 2:
The patent implements feedback mechanisms by calculating correlation between forward and backward trajectories and assessing reliability metrics. This feedback allows the system to automatically evaluate and integrate the most reliable tracking results, reducing the need for complex manual configuration and simplifying the overall system operation.
4Loss of information
If the correlation calculation and reliability assessment are performed between forward and backward trajectories, then significant trajectory information can be output even at low tracking accuracy levels, but the calculation complexity increases
Solution Approach 1:
The patent introduces correlation calculation and reliability assessment as intermediary processes between forward and backward tracking. These intermediaries evaluate the quality and consistency of trajectory data, enabling the system to output significant trajectory information even when individual tracking accuracy is low, while managing computational complexity through efficient correlation metrics.
Data Source
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Figure 4A~4C
AI summary
A trajectory analyzing apparatus includes a matching unit that calculates the correlation between a forward trajectory obtained by tracking a moving object over pictures along the forward direction of the time axis and a backward trajectory obtained by tracking a moving object over the pictures along the backward direction of the time axis and a result output unit that outputs trajectory information indicating at least one of the forward trajectory, the backward trajectory, and an integrated trajectory obtained by integrating the forward trajectory and backward trajectory and indicating the degree of reliability of the at least one trajectory based on the calculated correlation.