AR Focus Object Labeling for Social Network Formation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current augmented reality technologies lack effective methods for capitalizing on social networking advantages through focus-object-based labeling and communities of interest, limiting users' ability to connect and interact based on their real-world object interests.
Innovation Solution
A system that monitors augmented reality sessions, detects focus objects, labels them with indications of interest, and establishes geo-fenced social networks by associating labeled objects with users within a specified area, allowing users to connect and interact based on shared interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If augmented reality technologies use general-purpose computing devices, then device accessibility is improved, but social networking capabilities are limited
Solution Approach 1:
The system segments social networking functionality into modular components: focus object detection, labeling service, and community formation. This allows general-purpose devices to implement AR social networking by integrating only the necessary modules rather than requiring complex dedicated hardware.
Solution Approach 2:
A labeling service acts as an intermediary between the AR device and social networking functionality. The labeling service receives focus object data from general-purpose devices and returns labeled objects that enable social networking, thereby bridging the capability gap without requiring complex device modifications.
2Productivity
If focus objects are detected and labeled in real-time, then user connection efficiency is improved, but processing complexity increases
Solution Approach 1:
The labeling service serves as an intermediary that handles the complex processing of focus object detection and labeling. The AR device simply provides raw focus object data, and the labeling service returns processed labeled objects, distributing processing complexity away from the device.
Solution Approach 2:
The system performs preliminary labeling of focus objects as they are detected, rather than waiting for complete data collection. This real-time labeling enables immediate user connections based on shared interests without requiring complex post-processing.
3Adaptability or versatility
If geo-fenced social networks are established, then community relevance is improved, but system complexity increases
Solution Approach 1:
The system segments the social networking functionality into distinct services: focus object detection, labeling, and community formation. The geo-fenced community establishment is handled as a separate module that receives labeled objects and creates relevant communities, reducing overall system complexity.
Solution Approach 2:
The labeling service acts as an intermediary that prepares structured labeled object data, which then feeds into the community formation process. This intermediary layer simplifies the complexity of establishing geo-fenced networks by providing pre-processed, standardized input data.
Data Source
AI summary
According to one embodiment, a method, computer system, and computer program product for creating a social network in augmented reality (AR) based on focus objects is provided. The present invention may include monitoring an augmented reality session of a user; detecting focus objects of a user during the augmented reality session; labeling the detected focus objects with indications of interest; associating the labeled detected focus objects with additional users; and establishing, based on the labelled detected focus objects, a social network, where the social network contains focus objects sourced from additional users.