Information Processing for Context-Aware Augmented Reality Objects
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Solution Overview
Problem
Existing augmented reality technologies lack the ability to create composite spaces that effectively fuse the real and virtual worlds in a way that enhances user engagement and interest through personalized and dynamic interactions based on environmental and behavioral data.
Innovation Solution
An information processing device and method that acquires environmental and user behavior data to determine the type, display form, and position of virtual objects in real-time, using a mobile terminal with integrated sensors and cameras to generate augmented reality images that adapt to the user's surroundings and history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If virtual objects are displayed in augmented reality based on simple environment recognition, then the system is easy to implement, but the user engagement and interestingness are insufficient
Solution Approach 1:
The system changes multiple parameters simultaneously including object type selection based on environment category, display form selection based on user behavior history, and positioning based on spatial relationships. This multi-parameter approach creates highly adaptive AR experiences that respond to both environmental context and user preferences, resolving the contradiction between implementation simplicity and user engagement.
Solution Approach 2:
The system performs preliminary analysis of both environment characteristics and user behavior history before displaying virtual objects. By pre-processing environmental data to identify categories (natural, urban, indoor) and pre-analyzing user behavior patterns, the system prepares multiple candidate objects and their optimal display forms in advance, enabling quick and engaging AR rendering without complex real-time computation.
2Adaptability or versatility
If virtual objects are personalized based on user behavior history and environment data, then user engagement improves, but the system complexity increases
Solution Approach 1:
The system segments the personalization process into independent modules: environment recognition module that categorizes spatial context, user behavior analysis module that processes historical data, object selection module that matches objects to contexts, and display form determination module that adapts presentation based on user preferences. This modular segmentation reduces system complexity while maintaining comprehensive personalization capabilities.
Solution Approach 2:
The system introduces an intermediary processing layer that translates complex environment and user data into simplified selection criteria. This intermediary layer pre-processes environmental features and user behavior patterns to generate candidate object lists and optimal display parameters, reducing the computational burden on the final rendering system while enabling sophisticated personalization.
3Manufacturing precision
If the system acquires and processes multiple types of data (environmental and behavioral), then the quality of virtual content improves, but the data processing load increases
Solution Approach 1:
The system performs preliminary processing of environmental data to extract key categorical features (natural, urban, indoor) and preliminary analysis of user behavior history to identify preference patterns before AR rendering. By pre-computing these features and storing them in optimized formats, the system reduces real-time data processing requirements while maintaining high content quality that leverages both environmental context and user preferences.
Data Source
AI summary
Provided are an information processing device, an information processing method, and an information processing program that can provide a composite space or a virtual space having excellent interestingness. First information related to an environment of a space in which an object is caused to appear is acquired. Second information related to a behavior history of a user is acquired. A first element related to the object is determined based on the first information. A second element related to the object is determined based on the second information. The object to be caused to appear in the space is determined based on the first element and the second element.