Person Tracking Support Device Arrival Time Prediction
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Solution Overview
Problem
Current technologies lack effective support for tracking individuals across multiple cameras in facilities, leading to potential loss of sight of the tracked person.
Innovation Solution
A person tracking support device that acquires identification information and imaging times from multiple cameras, predicts the arrival time of the tracked person at specific areas, and notifies mobile terminal devices to enable observers to arrive before the person, with dynamic updates and strategic deployment of trackers based on predicted ratios and feature information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple cameras are used to track a person, then the reliability of tracking is improved, but the device complexity increases
Solution Approach 1:
The system segments the tracking function into multiple independent camera units distributed throughout the facility. Each camera independently captures images and the central device processes information from multiple cameras to maintain continuous tracking, dividing the complex tracking task into manageable segments that improve reliability without overwhelming system complexity
Solution Approach 2:
The person tracking support device serves multiple functions: it receives images from multiple cameras, identifies tracked persons using face recognition, calculates movement information, predicts arrival times, and notifies mobile terminals. This multi-functionality consolidates what would otherwise require separate systems into a single universal platform, improving reliability while managing complexity
2Measurement precision
If the predicted arrival time is calculated based on multiple camera data, then the measurement precision is improved, but the loss of time increases
Solution Approach 1:
The system performs preliminary actions by pre-calculating distances between cameras and storing camera position information in advance. When a tracked person is detected, the device immediately retrieves pre-stored data and performs calculations, avoiding time-consuming real-time measurements and reducing calculation time while maintaining precision
Solution Approach 2:
The system uses feedback from multiple camera detections to continuously refine arrival time predictions. By incorporating real-time position data from successive camera detections, the device adjusts predictions dynamically, improving accuracy while using efficient algorithms that minimize calculation time
Data Source
AI summary
A person tracking support device includes a processor. The processor acquires identification information of a tracked person identified from a face image of a person imaged by a first camera, and a first time at which the tracked person is imaged by the first camera, and also acquires a second time at which the tracked person is imaged by a second camera positioned away from the first camera, predicts a time at which the tracked person reaches a specific area on the basis of an elapsed time from the first time to the second time and a distance from the first camera to the second camera, and notifies a mobile terminal device possessed by each of a plurality of observers of the identification information of the tracked person, the specific area, and the time predicted.