Radar-Guided Camera Wake-Up for 3D ROI Surveillance
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Solution Overview
Problem
Existing video surveillance systems require a secondary camera or satellite imagery to convert 2D image coordinates into 3D real-world coordinates for designating regions of interest, which can be expensive and require user location sharing with third parties.
Innovation Solution
A video surveillance system that uses radar point cloud data to determine a region of interest (ROI) and converts 2D image coordinates into 3D real-world coordinates using a ground plane equation, eliminating the need for a secondary camera.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a secondary camera or satellite imagery is used to convert 2D image coordinates into 3D real-world coordinates, then the system can accurately designate regions of interest, but the system becomes more expensive and requires user location sharing with third parties
Solution Approach 1:
The patent extracts the coordinate conversion function from external dependencies (secondary cameras or satellite imagery) and implements it using only the primary radar system's point cloud data. By taking out the conversion capability from external sources and embedding it within the radar system itself, the patent eliminates the need for additional hardware while maintaining accuracy.
Solution Approach 2:
The radar system performs self-service by using its own point cloud data to enable 2D to 3D coordinate conversion. Instead of requiring external assistance from secondary cameras or satellite services, the radar system leverages its intrinsic capabilities to provide the conversion function, thereby reducing system complexity and cost.
2Measurement precision
If a secondary camera or satellite imagery is used to convert 2D image coordinates into 3D real-world coordinates, then the system can accurately designate regions of interest, but the system requires user location sharing with third parties
Solution Approach 1:
The patent removes the requirement for third-party satellite imagery services and user location sharing by extracting the coordinate conversion capability from external sources. The system now uses only locally available radar point cloud data, eliminating data privacy risks associated with sharing location information with third parties.
Solution Approach 2:
The system performs self-service coordinate conversion using its own radar data without requiring external services. This self-contained approach eliminates the need for users to share their location with third parties, thereby removing the associated data privacy risks while maintaining accurate coordinate conversion.
3Measurement precision
If a moving camera is used to capture the depth of an environment, then the system can convert 2D image coordinates into 3D real-world coordinates, but the system becomes more complex and expensive
Solution Approach 1:
The patent extracts the depth measurement and coordinate conversion capability from a moving camera system and implements it using stationary radar point cloud data. By taking out the depth measurement function from the camera system and embedding it in the radar system, the patent eliminates the need for moving camera mechanisms while maintaining 3D spatial understanding.
Solution Approach 2:
The patent replaces the mechanical moving camera system with a stationary radar system that uses point cloud data to achieve the same depth measurement and coordinate conversion functions. This substitution eliminates the mechanical complexity of moving cameras while maintaining the desired measurement capabilities.
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
This approach reduces costs and enhances user experience by allowing ROI designation from the user's perspective without requiring satellite imagery, thus avoiding potential errors and third-party interactions.
Implementation Method 1
the transceiver circuitry is configured to transmit and receive radar signals. In an implementation, the processing circuitry receives radar signals from the transceiver circuitry to identify a location of an object moving within the scene
Data Source
AI summary
Various embodiments of the present disclosure relate to video surveillance systems, and in particular, to determining when to wake-up a camera based on gathered radar data. In an example embodiment a system including transceiver circuitry and processing circuitry is provided. The transceiver circuitry is configured to transmit and receive radar signals. The processing circuitry is coupled with the transceiver circuitry and is configured to generate point cloud data associated with a scene and obtain a radar-space region of interest (ROI) based on the point cloud data. Further, the processing circuitry is configured to identify a location of an object moving in the scene based at least on a radar signal received by the transceiver circuitry. The processing circuitry is also configured to determine to wake-up a camera based on the location of the object in the scene and the radar-space ROI.