Image Sequence Interpolation via Keypoint Transformation
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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 storage.
Innovation Solution
The method involves obtaining a sequence of images captured along a camera translation, identifying keypoints, tracking them, computing transformations using a RANSAC algorithm, and determining an optimal subset of transformations for on-the-fly interpolation, allowing for efficient generation of artificially rendered frames between captured frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dense depth map or optical flow map is used for interpolation or extrapolation, then the scene structure is described accurately, but processing speed and transfer rates are reduced
Solution Approach 1:
The patent extracts only the essential transformation parameters (translation, rotation, scale) from the full dense depth map or optical flow map. Instead of processing all pixel data, it identifies and utilizes only the key transformation characteristics needed for view synthesis, significantly reducing data volume while maintaining interpolation accuracy.
Solution Approach 2:
The patent performs preliminary estimation of transformation parameters between image frames before the actual interpolation process. By pre-computing these transformation characteristics and storing them for later use, it avoids the need to process dense depth or optical flow maps during real-time interpolation, thereby improving processing speed.
2Measurement precision
If dense depth map or optical flow map is used for interpolation or extrapolation, then the scene structure is described accurately, but transfer rates over network are reduced
Solution Approach 1:
The patent extracts only the essential transformation parameters (translation, rotation, scale) from the full dense depth map or optical flow map. Instead of processing all pixel data, it identifies and utilizes only the key transformation characteristics needed for view synthesis, significantly reducing data volume while maintaining interpolation accuracy.
3Device complexity
If traditional 2D flat images are used, then storage and processing are simple, but the ability to reproduce memories and events with high fidelity is limited
Solution Approach 1:
The patent transforms static 2D images into dynamic 3D viewable content by computing transformation parameters that enable virtual camera movements. The system allows users to navigate through synthesized intermediate views, converting fixed 2D representations into interactive 3D experiences that preserve spatial relationships and enable high-fidelity memory reproduction.
Solution Approach 2:
The patent adds the third dimension to traditional 2D images by estimating depth information and transformation parameters from multiple 2D frames. This enables the creation of 3D virtual views from 2D input, allowing users to explore scenes from different angles and perspectives while maintaining compatibility with standard 2D image formats.
Data Source
AI summary
Various embodiments of the present invention relate generally to systems and processes for interpolating images of an object. According to particular embodiments, a sequence of images is obtained using a camera which captures the sequence of images along a camera translation. Each image contains at least a portion of overlapping subject matter. A plurality of keypoints is identified on a first image of the sequence of images. Each keypoint from the first image are kept track of to a second image. Using a predetermined algorithm, a plurality of transformations are computed using two randomly sampled keypoint correspondences, each of which includes a keypoint on the first image and a corresponding keypoint on the second image. An optimal subset of transformations is determined from the plurality of transformations based on predetermined criteria, and transformation parameters corresponding to the optimal subset of transformations is calculated and stored for on-the-fly interpolation.