Omni-directional Image Synthesis via Weighted Projection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current VR and AR technologies face challenges in seamlessly providing omni-directional images across various user movement positions, as it is impractical to prepare for all possible user movements, making it difficult to obtain omni-directional images corresponding to predicted user movements through capturing.
Innovation Solution
A method and apparatus that generate new omni-directional images with different centers by projecting and combining two-dimensional images from multiple omni-directional images captured by cameras with distinct centers, using a processor to align and weight the images for accurate representation across various viewpoints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple omni-directional images are captured to cover all possible user movement positions, then the completeness of coverage is improved, but the device complexity and data processing load increase significantly
Solution Approach 1:
The patent pre-generates a limited set of omni-directional images from fixed camera positions before the user actually moves. These pre-captured images are stored and later combined through image processing to synthesize views from intermediate positions. This approach prepares necessary data in advance without requiring cameras at all possible user positions, thus reducing system complexity while maintaining coverage completeness.
Solution Approach 2:
The patent creates virtual copies of omni-directional images by projecting and recombining images from fixed camera positions. Instead of placing physical cameras at every possible user position, the system generates synthetic image representations through geometric projection and blending algorithms. This copying approach allows the system to provide seamless omni-directional views from any position using a limited set of actual captured images.
2Adaptability or versatility
If omni-directional images are captured from multiple fixed positions, then the ability to provide seamless VR/AR experience is improved, but the power consumption and processing load increase
Solution Approach 1:
The system performs image combination and processing operations in advance, before the user actually views the content. By pre-combining images from multiple fixed positions into a unified omni-directional representation, the system reduces the computational burden during actual VR/AR usage. This preliminary processing approach maintains seamless experience quality while lowering real-time power consumption.
Solution Approach 2:
The patent extracts and utilizes only the essential image data from multiple fixed positions that is needed to reconstruct omni-directional views. Rather than processing all captured data in real-time, the system identifies and extracts key projection information during pre-processing, storing only the necessary combined representations. This extraction approach maintains experience quality while reducing processing load and power consumption during usage.
3Productivity
If a limited number of omni-directional images are used, then the system load is reduced, but the accuracy of representing all user viewpoints deteriorates
Solution Approach 1:
The patent creates accurate virtual projections of images from fixed camera positions onto a unified spherical coordinate system. Through geometric projection algorithms, the system copies and transforms image data while preserving spatial relationships and viewpoint accuracy. This mathematical copying process ensures that even with limited physical camera positions, the synthesized omni-directional images accurately represent intermediate viewpoints that users might encounter.
Solution Approach 2:
The patent combines multiple omni-directional images from fixed positions into a single unified representation using weighted blending and projection techniques. By merging the information from multiple fixed views through careful interpolation and weighting, the system reconstructs accurate intermediate perspectives. This combining approach allows accurate viewpoint representation with fewer physical cameras, maintaining productivity while improving viewpoint coverage accuracy.
Data Source
AI summary
A method for processing information regarding omni-directional images is provided. The method includes generating a first two-dimensional (2D) image projected from a first omni-directional image, generating a second 2D image projected from the second omni-directional image, generating a third 2D image corresponding to a 2D image projected from a third omni-directional image, generating a fourth 2D image projected from a fourth omni-directional image, generating a fifth 2D image corresponding to a 2D image projected from a fifth omni-directional image generating a sixth 2D image corresponding to a 2D image projected from a sixth omni-directional image, and generating a seventh 2D image corresponding to a 2D image projected from a seventh omni-directional image, a weight for the first omni-directional image, a weight for the second omni-directional image, and a weight for the fourth omni-directional image.