AR Content Generation Using Participant Device Aggregation
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Solution Overview
Problem
Current Augmented Reality (AR) systems fail to capture and display event memories effectively, as they only provide a first-person perspective and cannot utilize camera feeds from participants to create a third-person view, lacking the use of Ultra-wideband (UWB) sensors or Simultaneous Localization and Mapping (SLAM) engines for positional information and database correlation of image frames.
Innovation Solution
A method and system that aggregate camera feeds and image frames using participant device location information to generate a third-person AR content view, incorporating UWB sensors and SLAM engines for scene localization, and create a database with correlated parameters to enable users to relive events from multiple perspectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only first-person perspective recordings are used in AR systems, then the system simplicity is maintained, but the emotional capture and event memory effectiveness deteriorates
Solution Approach 1:
The system segments the recording perspective into multiple independent components: first-person view from the AR device, third-person view from participant devices, and emotional data from sensors. Each segment is captured separately and then integrated to provide comprehensive event memory without requiring a complete system redesign
Solution Approach 2:
Participant devices act as intermediaries between the AR system and the event being recorded. These devices capture third-person perspectives and emotional data, mediating the information flow back to the AR system to enhance emotional capture without directly modifying the core AR recording mechanism
2Loss of information
If camera feeds from multiple participant devices are aggregated to create third-person view, then the event memory completeness is improved, but the data processing complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-processing camera feeds from participant devices as they are captured, organizing them with temporal and spatial metadata before aggregation. This preliminary organization reduces the complexity of subsequent integration and enables efficient third-person view generation
Solution Approach 2:
The system transitions from two-dimensional image processing to three-dimensional spatial reconstruction by incorporating depth information and positional data from multiple participant devices. This dimensional enhancement enables comprehensive event memory reconstruction while providing structured data that simplifies processing through geometric constraints
3Measurement precision
If UWB sensors and SLAM engines are used to obtain positional information, then the third-person view accuracy is improved, but the device requirements and complexity increase
Solution Approach 1:
The system employs multi-functional participant devices that simultaneously perform camera recording, UWB positioning, and SLAM processing. These universal devices handle multiple functions without requiring separate specialized equipment, reducing overall system complexity while maintaining high measurement precision for third-person view generation
Data Source
AI summary
Provided is a method for generating Augmented Reality (AR) content that includes: receiving a plurality of image frames of at least one scene captured by a plurality of participant devices in an AR or a Virtual Reality (VR) environment; storing the plurality of image frames and metadata associated with the plurality of image frames, in a database; receiving an AR content generation request to generate an AR content view of a user in the AR/VR environment, the AR content generation request including an identifier (ID) of the user and information of the at least one scene; retrieving a set of image frames from a plurality of stored image frames in the database based on the ID of the user, the information of the at least one scene, and metadata associated with the set of image frames, the set of images including the user in the at least one scene in the AR/VR environment; generating the AR content view of the user by combining the set of image frames retrieved from the database, based on the metadata associated with the set of image frames; and displaying the AR content view.