AR Item Rendering via Environmental Analysis
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Solution Overview
Problem
Conventional augmented reality systems face challenges in effectively displaying virtual content that fits within an immersive real-world environment, leading to inefficient use of computing resources and potential incorrect user input due to the need to render and view multiple three-dimensional models of items.
Innovation Solution
A method and system that recognizes physical items in a real-world environment and analyzes their characteristics to determine user preferences, allowing for the rendering of virtual items that match these characteristics, thereby improving user experience and reducing computational resource usage by displaying only relevant and compatible items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple three-dimensional models of items are rendered and displayed in an augmented reality environment, then the user can view different items to find one that fits the real-world environment, but this unnecessarily utilizes computing resources such as processing cycles, memory, and network bandwidth
Solution Approach 1:
The system performs preliminary analysis of the real-world environment characteristics (space, lighting, existing decor) before rendering any 3D models. User preferences are also analyzed in advance. This preliminary preparation enables the system to directly generate and display only the most compatible item recommendations, avoiding the need to render and display multiple unrelated 3D models, thus reducing computing resource consumption while maintaining adaptability.
2Adaptability or versatility
If multiple three-dimensional models of items are rendered and displayed in an augmented reality environment, then the user can view different items to find one that fits the real-world environment, but this results in inadvertent or incorrect user input to the wearable device
Solution Approach 1:
The system incorporates feedback mechanisms where user interactions with rendered items (such as viewing time, selection preferences, or explicit feedback) are analyzed to refine and update user preference profiles. This feedback loop allows the system to progressively improve the accuracy of item recommendations, reducing the likelihood of inadvertent or incorrect user input by presenting increasingly relevant options that truly match user needs and environmental constraints.
3Productivity
If the system renders three-dimensional models of items that do not fit the real-world environment, then more items can be displayed for user consideration, but this unnecessarily utilizes computing resources and may lead to incorrect user input
Solution Approach 1:
The system performs preliminary analysis of the real-world environment characteristics (space dimensions, lighting conditions, existing decor style) before rendering any 3D models. User preferences are also analyzed in advance. This preliminary preparation enables the system to directly generate and display only the most compatible item recommendations, avoiding the need to render and display multiple unrelated 3D models, thus reducing computing resource consumption while maintaining adaptability.
Data Source
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AI summary
The disclosed technologies identify opportunities to display relevant three-dimensional ("3D") model data within a real-world environment as a user wears a wearable device. The 3D model data can be associated with objects, items, and the 3D model data rendered for display is relevant in the sense that the items are determined to be of interest to the user and items fit within the real-world environment in which the user is currently located. For instance, the techniques described herein can recognize items typically found in a kitchen or dining room of a user's house, an office space at user's place of work, etc. The characteristics of the recognized items can be identified and subsequently analyzed together to determine preferred characteristics of a user. In this way, the disclosed technologies can retrieve and display an item that correlates to (e.g., matches) the preferred characteristics of user.