Video Behavior Prediction Using Person-Object Relationship Analysis
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Solution Overview
Problem
Existing behavior recognition technologies are limited to recognizing behaviors that have already occurred, making it difficult to take timely countermeasures, and fail to predict potential future situations that may require intervention.
Innovation Solution
An information processing system that combines behavior analysis with context sensing to identify relationships and predict future behaviors by analyzing video data using machine learning models for skeleton and facial expression recognition, enabling the detection of potential future events such as shoplifting, illness, or crime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If behavior recognition technology is used to recognize current or past behaviors, then behavior detection capability is improved, but the ability to predict future behaviors requiring countermeasures deteriorates
Solution Approach 1:
The system performs preliminary analysis of behavior patterns, relationships between persons and objects, and contextual factors to predict future behaviors before they occur. This allows countermeasures to be prepared in advance, transforming reactive response into proactive prevention and eliminating the time loss between detection and intervention.
2Device complexity
If simple behavior recognition is implemented, then system complexity is reduced, but the ability to identify situations requiring countermeasures deteriorates
Solution Approach 1:
The system segments the behavior analysis into distinct components: behavior pattern recognition, relationship identification (between persons and objects), and contextual factor analysis. Each component processes specific aspects independently, then integrates results to predict future behaviors. This segmentation maintains manageable system complexity while achieving comprehensive and reliable situation identification.
Data Source
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AI summary
An information processing apparatus acquires (51) video data that includes target objects including a person and an object, first identifies (52) a relationship between the target objects in the acquired video data, by inputting the acquired video data to a first machine learning model, second identifies (53) a behavior of the person in the video data by using a feature value of the person included in the acquired video data, and predicts (54) one of a future behavior and a future state of the person by comparing the identified behavior of the person and the identified relationship with a behavior prediction rule that is set in advance.