Multi-Camera Person Matching with FPS-Synchronized Trajectory Tracking
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Solution Overview
Problem
Existing biometric authentication systems using multiple cameras with different shooting intervals face reduced accuracy due to the exclusion of images taken at intervals shorter than the set interval, leading to degraded person tracking and judgment accuracy, especially when multiple people are present and moving in different directions.
Innovation Solution
A method that involves setting a predetermined execution interval based on the minimum frame per second (fps) of the cameras, performing first and second image processing to calculate and track trajectories, and determining matching identities across cameras, ensuring high accuracy by synchronizing image processing with the lowest fps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing is performed using a unified fixed interval regardless of camera fps, then the system is simple to operate, but tracking accuracy deteriorates because images from high-fps cameras are excluded
Solution Approach 1:
The patent applies dynamics by making the image processing interval adaptive rather than fixed. Each camera's image processing interval is dynamically adjusted according to its specific fps, allowing the system to optimize tracking accuracy for each camera individually while maintaining overall system coherence through synchronization mechanisms.
Solution Approach 2:
The patent changes the processing interval parameter for each camera based on its fps capability. By adjusting this parameter dynamically, the system ensures that images are processed at optimal intervals for each camera, preventing accuracy loss due to exclusion of high-fps camera images while avoiding the complexity of a single unified processing schedule.
2Measurement precision
If images from all cameras are processed at their native intervals, then tracking accuracy is maximized, but the system becomes complex to synchronize and manage
Solution Approach 1:
The patent applies preliminary action by pre-establishing a synchronization mechanism that anticipates the timing of images from different cameras. The system prepares and coordinates processing intervals in advance, ensuring that images from cameras with different fps are processed in a coordinated manner without requiring complex real-time synchronization adjustments.
Solution Approach 2:
The patent introduces a synchronization mechanism as an intermediary that mediates between cameras with different fps. This intermediary coordinates the processing intervals of multiple cameras, allowing each camera to operate at its optimal fps while maintaining overall system synchronization and simplifying management through a central coordination layer.
3Measurement precision
If a single fixed processing interval is used for all cameras, then system management is simple, but person tracking accuracy deteriorates when multiple people move in different directions
Solution Approach 1:
The patent applies segmentation by dividing the image processing task into camera-specific intervals rather than using a single unified interval. Each camera is assigned its own processing interval based on its fps, allowing independent optimization for each camera's tracking needs while maintaining overall system coherence through synchronization.
Solution Approach 2:
The patent changes the processing interval parameter for each camera individually based on its fps characteristics. This parameter adaptation allows the system to maintain high tracking accuracy for multiple people moving in different directions by processing images at optimal intervals for each camera, avoiding the accuracy loss associated with fixed uniform intervals.
Data Source
AI summary
A determination method includes when first images in a time series photographed by a first camera every first time and second images in a time series photographed by a second camera every second time are acquired, calculating a trajectory of a person that is in each of the first images and a trajectory of a person that is in each of the second images, determining a third time according to a time for acquiring each of the first images from the first camera and a time for acquiring each of the second images from the second camera, and judging whether a person whose trajectory is calculated from an image of the first images corresponding to the third time after determined and a person whose trajectory is calculated from an image of the second images corresponding to the third time after determined are the same.