Segmented Volumetric AR from Existing Images and Videos
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Solution Overview
Problem
Existing augmented reality (AR) technologies struggle to create immersive experiences from existing images and videos, lacking the ability to dynamically adapt virtual content to real-world environments and user interactions.
Innovation Solution
A volumetric content presentation system that utilizes client and server-side functionalities to segment and render three-dimensional elements from images and videos, incorporating metadata and user inputs to create immersive AR experiences, and integrates with IoT devices for enhanced contextual interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional AR technologies are used to create AR experiences from existing images and videos, then the implementation is simpler, but the immersion and adaptability to real-world environments are insufficient
Solution Approach 1:
The system segments the input image into multiple regions of interest (ROIs) and processes each ROI independently to generate corresponding volumetric content items. This segmentation approach enables the system to handle complex scenes with multiple objects by breaking them down into manageable parts, improving adaptability to diverse real-world environments while maintaining systematic processing
Solution Approach 2:
The system transforms two-dimensional image data into three-dimensional volumetric content items, adding a spatial dimension to the AR experience. This dimensionality change enables more immersive and realistic virtual content that can be viewed from multiple angles and integrates better with the real-world environment, directly addressing the immersion deficiency of traditional AR
2Reliability
If volumetric content generation and real-time rendering are implemented, then immersion and user interaction are enhanced, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing by segmenting the image and identifying regions of interest before generating volumetric content. By pre-processing the input data and preparing ROI masks in advance, the system reduces the computational burden during the actual rendering phase, thereby improving user interaction quality while minimizing processing time delays
Solution Approach 2:
The system dynamically adjusts the processing pipeline based on the complexity of the input image and the number of identified ROIs. It can selectively process only the most significant regions or adjust the level of detail in volumetric generation, enabling flexible trade-offs between interaction quality and processing time depending on real-time requirements
3Adaptability or versatility
If multiple regions of interest are processed to generate multiple volumetric content items, then the AR experience becomes more comprehensive, but the device complexity and processing requirements increase
Solution Approach 1:
The system divides the complex task of processing the entire image into smaller, independent tasks by segmenting it into multiple regions of interest. Each ROI is processed separately to generate individual volumetric content items, which can then be composed into a comprehensive AR scene. This approach enhances the comprehensiveness of the AR experience by capturing multiple objects while managing processing requirements through modularization
Solution Approach 2:
The system implements a universal processing pipeline that can handle any number and type of regions of interest using the same core algorithms and methods. The ROI identification, volumetric generation, and rendering components are designed to be multi-functional, allowing the system to process diverse content (people, objects, scenes) uniformly, thereby improving comprehensiveness without proportionally increasing device complexity
Data Source
AI summary
A two-dimensional element is identified from one or more two-dimensional images. A volumetric content item is generated based on the two-dimensional element identified from the one or more two-dimensional images. A display device presents the volumetric content item overlaid on a real-world environment that is within a field of view of a user of the display device.