Separate-Device Aperture Fusion Using Localization for Low-Power XR Imaging
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Solution Overview
Problem
Existing XR devices face challenges in efficiently combining images from multiple cameras with different perspectives and properties, leading to power consumption issues due to high data processing demands and battery drain in portable devices.
Innovation Solution
A system for aperture fusion that normalizes image properties and generates a combined image by reconciling perspectives from multiple cameras, using localization information and machine learning techniques to create a unified view, while removing obstructions and adapting to dynamic changes in camera positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If images from multiple cameras are combined to provide greater perspective, then the viewing experience is improved, but the data processing demands increase leading to higher power consumption
Solution Approach 1:
The patent applies preliminary action by performing image normalization and alignment operations before the actual image combination process. The system pre-processes images from multiple cameras by normalizing their properties and aligning them to a reference viewpoint, which reduces the computational complexity during the fusion stage and thereby lowers overall power consumption while maintaining enhanced perspective capabilities
2Productivity
If high-power processing is used to combine images efficiently, then image fusion quality is improved, but battery life is reduced
Solution Approach 1:
The patent applies segmentation by dividing the image processing task into distinct stages: initial normalization, alignment to reference viewpoint, and final fusion. Each stage processes only necessary image data with optimized algorithms, avoiding redundant high-power operations while maintaining fusion quality, thus extending battery life without sacrificing productivity
Solution Approach 2:
The system dynamically adjusts processing parameters such as resolution, compression levels, and fusion algorithms based on scene complexity and device power state. By changing these parameters adaptively, the system maintains high fusion efficiency when needed while reducing power consumption during normal operation, thereby extending battery life
3Measurement precision
If continuous high-power processing is applied to maintain image quality, then image combination accuracy is improved, but energy efficiency deteriorates
Solution Approach 1:
The patent implements periodic action by updating image fusion at optimized intervals rather than continuously. The system monitors scene changes and only triggers high-precision processing when significant changes are detected, using lighter processing for stable scenes. This periodic approach maintains combination accuracy when needed while dramatically improving energy efficiency during stable conditions
Data Source
AI summary
Systems and techniques for combining images captured by two or more image sensors are disclosed. For example, a method can include obtaining a first image of a scene from a first image sensor of a first device. The method can include obtaining a second image including at least a portion of the scene from a second image sensor of a second device. The second image is transmitted over a communications link. The method can include determining a localization between the first device and the second device based on a relative pose between the first device and the second device. The method can include normalizing one or more image properties between the first image and the second image. The method can include generating, based on the localization and normalizing the one or more image properties, a third image based on the first image and the second image.