Behavior Analysis Apparatus Frame-Out Prediction
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Solution Overview
Problem
Existing behavior analysis technologies for manufacturing sites face accuracy issues due to frame-outs of individuals from camera images, which can occur under installation restrictions such as limited camera placement and viewing angles, leading to potential deterioration in personal posture detection and behavior analysis accuracy.
Innovation Solution
A behavior analysis apparatus that includes an image acquisition unit, person image extraction unit, person skeleton detection unit, frame-out determination unit, and notification unit to detect and prevent frame-outs by analyzing camera images and predicting potential frame-outs, thereby notifying individuals to adjust their position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If camera installation restrictions are imposed (limited placement and viewing angles), then device complexity and installation ease are improved, but measurement precision and reliability of behavior analysis deteriorate due to frame-outs
Solution Approach 1:
The system performs preliminary detection of frame-out conditions by analyzing the position of the person image area relative to the camera field angle boundaries. Before a complete frame-out occurs, the system detects when the person image approaches the boundary and predicts the frame-out event, allowing preventive notification to be issued.
Solution Approach 2:
The system continuously monitors the position of the person image area and provides feedback through notifications when frame-out conditions are detected or predicted. This feedback loop allows real-time correction of the person's position to maintain them within the camera field angle, thereby preserving measurement precision.
2Measurement precision
If camera field angle is reduced to focus on specific area, then measurement precision for that area is improved, but reliability of continuous behavior tracking deteriorates due to increased frame-out occurrences
Solution Approach 1:
The system uses the person skeleton detection to identify key body parts and predicts future frame-out events based on the person's movement trajectory. By detecting the tendency toward frame-out before it actually occurs, the system can issue timely notifications to prevent complete loss of the person from the field of view.
Solution Approach 2:
The system provides continuous feedback about frame-out risks by notifying the person when their image approaches the boundary of the camera field angle. This enables the person to adjust their position proactively, maintaining reliable continuous tracking while allowing the use of a focused camera field angle for precise posture detection.
Data Source
AI summary
Provided is a technology for preventing a frame-out of a person from an image acquired through a camera in a behavior analysis technology using the acquired image. A behavior analysis apparatus includes: an image acquisition unit; a person image extraction unit; a person skeleton detection unit; a person behavior analysis unit; a frame-out determination unit configured to determine a frame-out of the person toward an outside of the predetermined field angle as to one of whether or not the frame-out has occurred and whether or not the frame-out is predictable through use of any one of the person image area and the person skeleton; and a frame-out notification unit configured to notify the person of the determination in one of a case where the frame-out has occurred and a case where the frame-out is predictable.