Camera Region of Interest Auto-Setting via Mark Detection
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Solution Overview
Problem
Existing methods for setting a region of interest in camera monitoring systems require user input, leading to variability in detection accuracy due to user skill and require manual resetting when the camera viewpoint changes, causing performance deviations.
Innovation Solution
A method and apparatus that automatically detect marks in image frames from a camera to set and reset the region of interest without user input, using a mark detection unit and viewpoint change detection unit to ensure consistent and accurate detection of abnormal behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the region of interest is set relying on user input, then the system can be operated, but the detection accuracy varies due to user skill differences
Solution Approach 1:
The system automatically detects marks in the image frame and sets the region of interest without requiring user input. The mark detection unit identifies predefined marks (such as traffic signs, road markings, or other reference objects) and the region of interest setting unit automatically determines the ROI based on these detected marks, enabling the system to serve itself without human intervention for ROI configuration.
Solution Approach 2:
The manual operation of setting ROI by user input is replaced with an automated image processing system. The mark detection unit uses image processing techniques to detect marks in the camera feed, and the region of interest setting unit uses algorithmic logic to determine the ROI, substituting the mechanical/manual process with an automated computational system.
2Ease of operation
If the region of interest is manually set, then initial setup is simple, but the system requires continuous manual resetting when camera viewpoint changes
Solution Approach 1:
The system continuously monitors the image frame for mark detection and camera viewpoint changes. When a mark is detected or a viewpoint change is identified, the system automatically adjusts the region of interest settings, providing real-time feedback-based adaptation without requiring manual intervention for resetting.
Solution Approach 2:
The system pre-identifies marks in the environment that serve as reference points for ROI determination. By having these marks预先 detected and stored as reference information, the system can quickly recalculate and reset the ROI when viewpoint changes occur, without requiring time-consuming manual reconfiguration.
3Adaptability or versatility
If user input is required for setting ROI, then flexibility in configuration is achieved, but performance deviations occur due to user skill variations
Solution Approach 1:
The system changes from user-defined parameters to system-detected parameters for ROI configuration. Instead of relying on users to manually specify ROI boundaries based on their skill and judgment, the system automatically detects marks and calculates ROI parameters (position, size, shape) based on the detected mark locations and characteristics, ensuring consistent and reliable results.
Solution Approach 2:
The system creates a standardized method for ROI setting by copying the successful approach of mark-based detection. Rather than allowing varied user interpretations, the system uses a consistent algorithmic approach that copies the same detection and calculation logic for all ROI settings, ensuring uniformity and reliability across different operating conditions.
Data Source
AI summary
According to a first aspect of the present invention, a method for setting a region of interest may include: detecting a mark in an image frame photographed by a camera; and setting a region of interest using the detected mark.