Stereo Correspondence Smoothness Tool for Ambiguous Image Regions
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Solution Overview
Problem
Conventional stereo correspondence techniques fail to accurately determine correspondences in images with ambiguities such as lack of textures, repeated patterns, shadows, and view-point changes, leading to processing failures.
Innovation Solution
A user-defined region is indicated through a user interface to calculate stereo correspondence, allowing smoothness in disparities to be specified for pixels, using a smoothness tool to vary disparities smoothly and applying weights to ensure consistency, thereby overcoming ambiguities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional stereo correspondence techniques are used, then processing can be performed on textured regions, but processing fails on ambiguous regions (white walls, repeated patterns, shadows, view-point changes)
Solution Approach 1:
The patent applies local quality by allowing different regions of the image to have different smoothness constraints. Users can selectively apply smoothness constraints to specific regions (e.g., white walls, repeated patterns) while leaving other regions with standard constraints. This enables the system to handle ambiguous regions without compromising the overall stereo correspondence calculation reliability.
Solution Approach 2:
The system provides feedback by displaying the current stereo correspondence results and allowing users to interactively adjust smoothness constraints based on visual inspection. Users can identify ambiguous regions and apply local smoothness constraints, then view the updated results to verify improvement. This iterative feedback loop enhances both reliability and adaptability.
2Stability of the object's composition
If smoothness constraints are applied to all regions, then disparity smoothness is enforced everywhere, but this reduces the ability to handle local variations and ambiguities flexibly
Solution Approach 1:
Instead of applying uniform smoothness constraints across the entire image, the system allows users to selectively apply constraints to specific regions. This enables the system to enforce disparity smoothness where needed (e.g., textured regions) while maintaining flexibility in ambiguous regions (e.g., white walls, repeated patterns), thus resolving the contradiction between stability and adaptability.
Solution Approach 2:
The system dynamically adjusts smoothness constraints based on user input and image content. Users can interactively define which regions should have smoothness constraints and which should not, allowing the system to adapt its behavior to different imaging scenarios. This dynamic adjustment resolves the contradiction by making the smoothness enforcement flexible rather than rigid.
Data Source
AI summary
Stereo correspondence smoothness tool techniques are described. In one or more implementations, an indication is received of a user-defined region in at least one of a plurality of stereoscopic images of an image scene. Stereo correspondence is calculated of image data of the plurality of stereoscopic images of the image scene, the calculation performed based at least in part on the user-defined region as indicating a smoothness in disparities to be calculated for pixels in the user-defined region.