Multi-Camera Object Tracking via Homography Matrix
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing multi-camera object tracking systems face challenges in maintaining accurate tracking in complex environments due to occlusions, lighting variations, and overlapping fields of view, and they often require additional hardware and technologies like Wi-Fi and Bluetooth, which increase costs and complexity while introducing security vulnerabilities.
Innovation Solution
A multi-camera object tracking system that uses a processor and memory configured to receive identifiers and tracking information from overlapping video streams, determine positional information using a homography matrix, match objects based on minimum distance, and record identifiers in a correspondence table for analysis, thereby eliminating the need for supplementary technologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If supplementary technologies such as Wi-Fi and Bluetooth are integrated into the multi-camera tracking system, then tracking accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts and removes the supplementary technologies (Wi-Fi, Bluetooth, sensors) from the tracking system, relying solely on camera data processing. This eliminates the need for additional hardware while maintaining tracking functionality through advanced image analysis and coordinate transformation techniques.
Solution Approach 2:
The camera system is made multi-functional by enabling it to perform both object detection and tracking without additional specialized hardware. The system uses the camera's inherent capabilities combined with homography matrices and coordinate transformations to achieve accurate multi-camera tracking, making the camera serve multiple purposes.
2Measurement precision
If supplementary technologies such as Wi-Fi and Bluetooth are integrated into the multi-camera tracking system, then tracking accuracy is improved, but system cost increases
Solution Approach 1:
The patent extracts and removes the supplementary technologies (Wi-Fi, Bluetooth, sensors) from the tracking system, relying solely on camera data processing. This eliminates the need for additional hardware while maintaining tracking functionality through advanced image analysis and coordinate transformation techniques.
Solution Approach 2:
The system uses standard, widely-available camera equipment instead of expensive specialized tracking hardware. By leveraging common camera technology combined with software-based coordinate transformation, the system achieves accurate tracking at a fraction of the cost of systems using proprietary tracking devices.
3Measurement precision
If supplementary technologies such as Wi-Fi and Bluetooth are integrated into the multi-camera tracking system, then tracking accuracy is improved, but network security vulnerabilities increase
Solution Approach 1:
The patent extracts and removes the supplementary technologies (Wi-Fi, Bluetooth, sensors) from the tracking system, relying solely on camera data processing. This eliminates the need for additional hardware while maintaining tracking functionality through advanced image analysis and coordinate transformation techniques.
Solution Approach 2:
The system introduces homography matrices as an intermediary mathematical tool to enable accurate coordinate transformation between cameras without requiring direct communication or data exchange between multiple hardware components. This mathematical intermediary eliminates the need for networked supplementary technologies while achieving the same tracking objective.
4Measurement precision
If additional hardware such as Wi-Fi modules and Bluetooth beacons is added to the tracking system, then tracking accuracy is improved, but ease of installation and maintenance deteriorates
Solution Approach 1:
The patent extracts and removes the supplementary technologies (Wi-Fi, Bluetooth, sensors) from the tracking system, relying solely on camera data processing. This eliminates the need for additional hardware while maintaining tracking functionality through advanced image analysis and coordinate transformation techniques.
Data Source
AI summary
An aspect of the present disclosure provides a multi-camera object tracking system. The system includes at least one processor; and at least one memory including computer program code. The at least one processor, at least one memory and the computer program code are configured to allow the system to receive an identifier and tracking information associated with each detected object within an overlapping portion of a first video stream from a first camera and a second video stream from a second camera, the overlapping portion associated with partially overlapping fields of view of the first and second cameras, determine positional information of each detected object relative to a common coordinate system using the tracking information and a homography matrix associated with the partially overlapping fields of view of the first and second cameras, match one detected object in the first video stream with another detected object in the second video stream, based on a criterion of minimum distance between the detected objects, using the positional information of each detected object, associate the identifiers of the matched objects, and record the associated identifiers in a correspondence table for object tracking analysis.


