VR Interest Analysis System Using Hit Maps and Traffic Tracking
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Solution Overview
Problem
Existing systems lack the capability to effectively analyze and measure user interest in Virtual Reality (VR) images, particularly in terms of traffic patterns and object interactions, which hinders the understanding of visitor engagement in virtual museum, art gallery, and exhibition environments.
Innovation Solution
A system that tracks user traffic lines and object interactions within VR images, generating hit maps based on user selection history to analyze interest levels, allowing users to move to specific points and objects, and categorizing popular areas and objects for analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a system tracks user traffic lines and object interactions in VR images, then user interest analysis capability is improved, but system complexity increases
Solution Approach 1:
The system segments user interaction data into distinct components: traffic line tracking data, object interaction data, and selection history data. Each segment is processed independently by dedicated modules (traffic line analyzing module, object interaction analyzing module, hit map generating module), allowing complex analysis to be broken down into manageable parts that reduce overall system complexity while maintaining measurement precision.
2Measurement precision
If the system collects detailed selection history data from all users, then analysis accuracy is improved, but data processing load increases
Solution Approach 1:
The system extracts only the essential elements needed for analysis from raw user data: traffic line coordinates, object interaction events, and selection history. By extracting and storing only these critical data points rather than complete user session recordings, the system maintains high analysis accuracy while significantly reducing the quantity of data that needs to be processed and stored.
Solution Approach 2:
The system merges multiple data sources (traffic line tracking, object interaction detection, selection history) into a unified hit map structure. This consolidation allows the system to process diverse user behavior data through a single integrated analysis framework, reducing the overall data processing load while maintaining comprehensive analysis accuracy.
3Loss of information
If the system generates hit maps showing frequently visited areas, then user engagement insights are improved, but computational requirements increase
Solution Approach 1:
The system performs preliminary aggregation of user interaction data during the data collection phase, organizing traffic line and object interaction data into structured formats suitable for hit map generation. By preparing data in advance with appropriate grouping and aggregation, the system reduces the computational burden during the actual hit map generation process while ensuring comprehensive user engagement insights are captured.
Data Source
AI summary
The inventive concept relates to a system for analyzing a degree of interest in a VR image, which allows a user to freely move in a VR image, appreciate objects, and check information on the objects to make the user feel as if the user were actually making a visit, and analyzes a degree of interest of users by performing analysis and generating a hit map.