Building Radar-Camera Surveillance with Sphere-to-Plane Homography
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Solution Overview
Problem
Conventional building surveillance systems require a high number of cameras, leading to excessive costs, installation time, and calibration efforts, and struggle with poor visibility conditions and high false alarm rates, often necessitating human intervention.
Innovation Solution
A building radar-camera surveillance system that integrates radar and camera systems with AI classification networks, enabling autonomous object detection, classification, and tracking, reducing the need for numerous cameras and human oversight.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a high number of cameras are used to capture all areas of a building, then coverage completeness is improved, but system cost and installation time increase excessively
Solution Approach 1:
The patent combines radar and camera systems into an integrated surveillance platform where radar provides detection and tracking capabilities while cameras provide visual confirmation. This merging allows the system to achieve comprehensive coverage with fewer camera units by leveraging radar's all-weather detection capabilities to guide and supplement camera positioning.
Solution Approach 2:
The radar system performs multiple functions including detection, tracking, and guidance of camera positioning. By using radar for both primary surveillance and camera control, the system eliminates the need for numerous dedicated cameras, reducing overall system complexity while maintaining comprehensive monitoring coverage.
2Ease of manufacture
If conventional camera systems are used, then installation is simpler, but calibration requires significant technician time and expertise
Solution Approach 1:
The system implements automatic calibration algorithms that use radar data to self-adjust camera positioning and parameters without requiring extensive manual intervention. The radar-camera integration enables the system to automatically correlate detection data with visual data, performing calibration in the field with minimal technician involvement.
Solution Approach 2:
The system uses feedback loops where radar tracking data continuously informs camera positioning and calibration adjustments. This real-time feedback mechanism allows the system to automatically optimize its calibration based on actual performance data, reducing the need for manual calibration procedures.
3Device complexity
If camera-only surveillance is used, then system cost is lower, but effectiveness in poor visibility conditions (night, fog, rain) deteriorates
Solution Approach 1:
The system creates a composite surveillance solution combining radar and camera technologies, leveraging the complementary strengths of each. Radar provides reliable detection in all weather conditions while cameras provide detailed visual information when conditions permit, creating a robust multi-modal surveillance system.
Solution Approach 2:
The system dynamically switches between radar-primary and camera-primary operation modes based on environmental conditions. In poor visibility conditions, radar becomes the primary detection mechanism while cameras provide supplementary visual data when available, allowing the system to adapt its operational characteristics to maintain effectiveness across varying conditions.
4Reliability
If numerous cameras are deployed, then surveillance coverage is improved, but false alarm rate increases requiring human intervention
Solution Approach 1:
The radar system acts as an intermediary that pre-screens and filters targets before they are passed to the camera subsystem for detailed analysis. By using radar to identify and track potential targets of interest, the system reduces the volume of data requiring camera analysis and human review, thereby reducing false alarms while maintaining comprehensive surveillance coverage.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides accurate, real-time object detection and classification, reduces false alarms, and operates effectively in various weather conditions, offering a cost-effective and efficient surveillance solution.
Implementation Method 1
A building radar-camera surveillance system that integrates radar and camera systems
Data Source
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AI summary
A building radar-camera system includes a camera configured to capture one or images, the one or more images including first locations within the one or more images of one or more points on a world-plane and a radar system configured to capture radar data indicating second locations on the world-plane of the one or more points. The system includes one or more processing circuits configured to receive a correspondence between the first locations and the second locations of the one or more points, generate a sphere-to-plane homography, the sphere-to-plane homography translating between points captured by the camera modeled on a unit-sphere and the world-plane based on the correspondence between the first locations and the second locations, and translate one or more additional points captured by the camera or captured by the radar system between the unit-sphere and the world-plane based on the sphere-to-plane homography.