Gaze Position Detection for Spontaneous Interest Determination
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Solution Overview
Problem
Existing techniques fail to accurately determine whether a person's interest in a product is spontaneous or influenced by others, as they do not account for external factors such as surrounding people's movements and interactions.
Innovation Solution
An interest degree determination device that uses image information to detect a user's gaze position and determines if it is affected by nearby users, storing the determination results alongside the gaze position for association, employing various checks like movement, gestures, and facial changes to differentiate between spontaneous and influenced interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If gaze position detection is performed without considering surrounding users, then the detection process is simple, but the accuracy of determining genuine interest is poor
Solution Approach 1:
The detection process is segmented into multiple independent analysis modules: gaze position detection, user state detection (face direction, gestures, movements), and influence determination. Each module processes specific aspects separately, allowing comprehensive analysis without overwhelming system complexity. The segmentation enables parallel processing of different user attributes while maintaining overall system manageability.
Solution Approach 2:
The system performs preliminary detection of user states (face direction, gestures, movements) before making the final determination of genuine interest. By pre-processing and storing user state information, the system prepares data in advance that facilitates faster and more accurate interest determination when needed, reducing real-time computational burden.
2Measurement precision
If multiple user attributes are detected to determine influence, then the determination accuracy improves, but the processing time increases
Solution Approach 1:
User state attributes (face direction, gestures, movements) are detected and stored in advance before the influence determination is needed. This preliminary detection and storage of data eliminates the need for real-time multi-attribute analysis when determining influence, significantly reducing processing time while maintaining high determination accuracy through pre-collected comprehensive data.
3Reliability
If comprehensive user behavior analysis is performed, then the reliability of marketing data improves, but the system complexity increases
Solution Approach 1:
The comprehensive user behavior analysis system is divided into separate functional modules: gaze detection unit, user state detection unit (analyzing face direction, gestures, movements), and influence determination unit. Each module handles specific aspects of behavior analysis independently, enabling reliable comprehensive analysis while keeping individual module complexity manageable and the overall system structured.
Solution Approach 2:
The image processing device performs multiple functions using a unified system architecture: it detects gaze positions, analyzes user states (face direction, gestures, movements), determines influence relationships, and generates marketing data. This multi-functional approach achieves comprehensive behavior analysis through a single integrated system rather than multiple separate systems, reducing overall complexity while maintaining reliability.
Data Source
AI summary
An interest degree determination device detects a gaze position of a first user included in a plurality of users on the basis of image information. When a second user other than the first user is present in the vicinity of the first user, the interest degree determination device determines whether the gaze position of the first user has been affected by the second user. The interest degree determination device stores a determination result of a determination unit and the gaze position of the first user in a storage unit so as to be associated with each other.