Image-Based Subject State Recognition for Screen Cutoff and Self-Shielding
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Solution Overview
Problem
Existing image processing methods struggle to accurately identify the state of a subject when some parts are not detected due to being cut off the screen or shielded by other objects, leading to difficulties in distinguishing between self-shielding and being cut off, which results in incorrect recognition and potential false alarms.
Innovation Solution
An image processing apparatus and method that includes detecting predetermined parts of a subject, estimating the cause of failed detection, and determining the subject's state based on detected parts and estimated causes, using a system comprising a camera, analysis server, and terminal device to classify and recognize abnormal behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If image processing detects parts of a subject to recognize the state of the subject, then recognition capability is improved, but detection accuracy deteriorates when parts are cut off or shielded
Solution Approach 1:
The system performs preliminary actions by detecting the screen edges and determining the subject's position relative to the screen before the actual state recognition process. This preliminary positioning enables the system to anticipate which body parts might be cut off or shielded, allowing it to adjust its detection strategy accordingly and maintain accurate state recognition even when parts are missing.
Solution Approach 2:
The invention transitions from two-dimensional image detection to three-dimensional spatial reasoning by inferring the subject's position in 3D space relative to the camera and screen. By calculating distances and positions in three dimensions, the system can determine whether missing parts are due to screen cutoff or self-shielding, thereby resolving the detection accuracy problem while maintaining recognition capability.
2Reliability
If the system detects subject parts to determine state, then state recognition is improved, but false alarms increase due to inability to distinguish self-shielding from screen cutoff
Solution Approach 1:
The system performs preliminary detection of screen edges and subject positioning before state recognition. By establishing the subject's spatial relationship with the screen boundaries in advance, the system can pre-determine whether missing body parts are due to screen cutoff or self-shielding, thereby preventing false alarms during the actual state recognition process.
Solution Approach 2:
The invention introduces an intermediary analysis step that examines the spatial relationship between the subject, camera, and screen. This intermediary process determines the cause of undetected parts by calculating whether they fall within the screen boundaries or are obscured by the subject's own body, thereby mediating between raw detection data and final state recognition to eliminate false alarms.
3Adaptability or versatility
If the system processes images to recognize subject state, then recognition function is improved, but system complexity increases due to additional analysis requirements
Solution Approach 1:
The system segments the complex recognition task into distinct modular components: screen edge detection, subject positioning, cutoff determination, self-shielding determination, and state recognition. Each module handles a specific aspect of the problem independently, making the overall system more manageable and easier to implement despite the increased functionality.
Data Source
AI summary
An image processing apparatus includes detecting means for detecting a plurality of predetermined parts of a subject from an image, estimating means for estimating a cause of failed detection if any of the plurality of predetermined parts is not detected in a result of the detection made by the detecting means, and determining means for determining a state of the subject based on a part detected by the detecting means and the cause estimated by the estimating means.