Scene Scan Alignment via Similarity Transform
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Solution Overview
Problem
Existing panorama creation programs are unable to stitch photographic images captured from different optical centers due to parallax error, as they require images to be captured from a single perspective, making it impossible to align images perfectly when captured from varying viewpoints.
Innovation Solution
A method that determines a similarity transform, including rotation, scaling, and translation factors, to align common features between photographic images captured from different optical centers, allowing for the creation of a scene scan by positioning images such that their common features align, even when captured from different locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If photographic images are captured from different optical centers, then the versatility of image capture is improved, but the alignment precision deteriorates due to parallax error
Solution Approach 1:
The patent applies parameter changes by transforming the images through similarity transforms that adjust rotation, scaling, and translation parameters. This allows images captured from different optical centers to be mathematically transformed into a common coordinate system, resolving the alignment precision issue while maintaining capture flexibility
Solution Approach 2:
The patent introduces an intermediary coordinate system and similarity transform process that mediates between images from different optical centers. This intermediary transformation layer enables alignment without requiring the images to be captured from the same perspective, thus resolving the contradiction
2Manufacturing precision
If traditional panorama creation programs require images to be captured from a single perspective, then the alignment precision is improved, but the adaptability of the system deteriorates
Solution Approach 1:
The patent implements universality by creating a system that can handle both images from the same optical center and images from different optical centers. The similarity transform approach provides a unified method that works for various capture scenarios, making the system multi-functional and adaptable while maintaining precision
3Measurement precision
If images are stitched using common feature matching, then the alignment accuracy is improved, but the system fails when parallax error is present
Solution Approach 1:
The patent applies preliminary action by performing similarity transforms on the images before attempting feature matching and stitching. This pre-transformation step establishes a common reference frame, ensuring that subsequent feature matching operations are performed on already-aligned images, thus preventing parallax-related failures
Data Source
AI summary
Systems, methods, and computer storage mediums are provided for creating a scene scan from a group of photographic images. An exemplary method includes determining a set of common features for at least one pair of photographic images. The features include a portion of an object captured in each of a first and a second photographic image included in the pair. The first and second photographic images may be captured from different optical centers. A similarity transform for the at least one pair of photographic images is the determined. The similarity transform is provided in order to render the scene scan from each pair of photographic images. At least one of the rotation factor, the scaling factor, or the translation factor associated with the similarity transform is used to position each pair of photographic images such that the set of common features between a pair of, at least in part, align.