Viewpoint Interpolation Using Sparse Transform Parameters
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Solution Overview
Problem
Traditional digital media formats, such as 2D flat images, limit the ability to reproduce memories and events with high fidelity and require significant additional data for interpolation or extrapolation, leading to inefficiencies in processing speed and transfer rates.
Innovation Solution
The method involves applying a transform to estimate a path between two frames, generating an artificially rendered image by interpolating or extrapolating image information from these frames, and combining the information to create a smooth and immersive viewing experience, using techniques like homography, affine transformations, and weighted image information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional interpolation or extrapolation methods are used to generate artificially rendered images, then the viewing experience becomes more immersive and interactive, but the processing speed decreases and data transfer rates are reduced due to requiring significant additional data
Solution Approach 1:
The patent extracts only the essential transformation parameters (such as camera position, orientation, and focal length) needed for viewpoint interpolation, rather than requiring complete dense depth maps or optical flow maps for every pixel. This selective extraction of critical information maintains immersive viewing capabilities while dramatically reducing data requirements and processing overhead
Solution Approach 2:
The patent segments the complex scene transformation into discrete transformable elements (camera extrinsics and intrinsics), allowing independent processing and interpolation of each parameter. This segmentation enables efficient computation by handling only the essential degrees of freedom rather than processing entire image datasets
2Measurement precision
If dense depth maps or optical flow maps are used to describe scene structure, then the accuracy of interpolation improves, but the data redundancy increases leading to slower processing and network transfer
Solution Approach 1:
The patent applies partial action by computing transformation parameters only at key feature points or sparse locations rather than for every pixel in the image. This partial computation provides sufficient accuracy for viewpoint interpolation while avoiding the excessive data generation that would result from dense per-pixel processing
Solution Approach 2:
The patent transforms the problem from a 2D image-space operation to a 3D parameter-space operation by working with camera extrinsics and intrinsics. This dimensional transformation allows accurate scene reconstruction through interpolation of transformation parameters rather than direct manipulation of dense pixel data, significantly reducing data redundancy
3Adaptability or versatility
If multiple images are combined to create panorama or 3D images, then the immersion and interactivity improve, but the device complexity and computational requirements increase
Solution Approach 1:
The patent creates a universal transformation framework that can generate multiple types of immersive content (panoramas, 3D images, viewpoint interpolations) from the same set of transformation parameters. This multi-functional approach allows a single system to handle various immersive applications without requiring separate processing pipelines for each content type, thereby reducing overall system complexity
Data Source
AI summary
Various embodiments of the present invention relate generally to mechanisms and processes relating to artificially rendering images using viewpoint interpolation and extrapolation. According to particular embodiments, a method includes applying a transform to estimate a path outside the trajectory between a first frame and a second frame, where the first frame includes a first image captured from a first location and the second frame includes a second image captured from a second location. The process also includes generating an artificially rendered image corresponding to a third location positioned on the path. The artificially rendered image is generated by interpolating a transformation from the first location to the third location and from the third location to the second location, gathering image information from the first frame and the second frame by transferring first image information from the first frame to the third frame and second image information from the second frame to the third frame, and combining the first image information and the second image information.