Hybrid Camera Radar Tracking via Metadata Correlation
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Solution Overview
Problem
Non-overlapping camera tracking systems are inherently inaccurate when cameras are widely separated, and they struggle to handle situations where individuals linger or move in unexpected ways, such as multiple exit/entrance points.
Innovation Solution
A system that integrates calibrated camera and radar devices to track objects by generating and comparing metadata, including exit/entrance positions, motion vectors, and classification data of varying granularities, to determine if a new object is the same as the previously tracked object, and updates the track with transformed hybrid data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If cameras are widely separated to cover larger areas, then coverage area increases, but tracking accuracy deteriorates
Solution Approach 1:
The patent combines radar and camera systems into a hybrid tracking system. The radar device provides accurate tracking data for objects in its coverage area, while the camera device captures visual data. By merging the metadata from both devices and correlating their tracking information, the system maintains high tracking accuracy across wide coverage areas without requiring cameras to be closely spaced.
2Device complexity
If camera-only tracking is used to maintain system simplicity, then device complexity is reduced, but reliability deteriorates in handling unexpected movements
Solution Approach 1:
The patent changes the type of data parameters collected by using both radar and camera devices. The radar provides motion-based parameters (velocity, acceleration, distance changes) while the camera provides visual parameters (appearance, position). By correlating these different parameter types, the system achieves more reliable tracking of unexpected movements while maintaining manageable complexity through metadata-based processing.
3Measurement precision
If metadata from both radar and camera is integrated to improve tracking, then tracking accuracy improves, but device complexity increases
Solution Approach 1:
The patent introduces metadata as an intermediary layer between the radar and camera systems. Instead of directly integrating complex raw data from both devices, the system extracts and correlates metadata (tracking information, motion vectors, classification data) from each device. This intermediary metadata layer simplifies the integration process while maintaining high tracking accuracy through correlated data from both sensors.
Data Source
AI summary
A method, system and computer program product for intelligent tracking and transformation between interconnected sensor devices of mixed type is disclosed. Metadata derived from image data from a camera is compared to different metadata derived from radar data from a radar device to determine whether an object in a Field of View (FOV) of one of the camera and the radar device is an identified object that was previously in the FOV of the other of the camera and the radar device.