Virtual Viewpoint Image Generation via Depth-Aware Pixel Warping
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Solution Overview
Problem
Existing methods for generating virtual viewpoint images, such as 3D warping and disparity-based techniques, face challenges in providing smooth 6-degree of freedom (DoF) images due to issues like crack formation and scene distortion, especially when dealing with complex motions and varying depth values.
Innovation Solution
The method involves warping pixels from input viewpoint images to a virtual viewpoint coordinate system, mapping super-pixels based on depth value differences, and blending pixels using weights determined by depth value distribution and distance, to create a high-quality virtual viewpoint image that reduces blurring and distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If 3D warping method is used to generate virtual viewpoint image, then viewpoint image can be generated at virtual location, but crack formation and scene distortion occur due to depth variations
Solution Approach 1:
The patent segments the image processing into multiple stages: initial warping to generate virtual viewpoint image, followed by crack detection to identify problematic regions, and selective inpainting to repair only the detected cracks. This segmentation allows precise correction of distortions without affecting the entire image.
Solution Approach 2:
The patent introduces an intermediary crack detection module that acts as a mediator between the warping process and the final image output. This intermediary detects and flags crack regions, enabling targeted repair through inpainting while preserving the overall warping results.
2Ease of operation
If disparity-based method is used to generate virtual viewpoint image, then pixel movement is simplified, but smooth 6-DoF image generation is difficult under complex motions
Solution Approach 1:
The patent employs dynamic crack detection that adapts to different motion conditions. The crack detection algorithm dynamically adjusts its parameters based on the complexity of motion, enabling the system to handle various motion scenarios from simple to complex while maintaining ease of operation through automated adaptation.
Solution Approach 2:
The patent changes processing parameters dynamically based on motion complexity. The crack detection and inpainting parameters are adjusted according to the detected motion characteristics, allowing the system to maintain simplicity in operation while adapting to complex motion scenarios through parameter optimization.
3Measurement precision
If deep learning-based crack detection is used, then crack detection accuracy is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary crack detection using a computationally efficient method before applying deep learning-based refinement only to suspected crack regions. This preliminary action reduces the overall processing time by limiting expensive deep learning computations to only the necessary areas rather than processing the entire image.
Solution Approach 2:
The patent applies deep learning-based crack detection selectively to regions where cracks are likely to occur, rather than processing the entire image uniformly. This partial action approach maintains high detection accuracy in critical areas while reducing overall computational complexity and processing time.
4Manufacturing precision
If inpainting is applied to repair crack regions, then image quality is improved, but processing complexity increases
Solution Approach 1:
The patent applies inpainting selectively only to detected crack regions rather than processing the entire image. This local quality approach concentrates computational resources on areas where improvement is needed, enhancing image quality while minimizing overall processing complexity by leaving unaffected regions unchanged.
Data Source
AI summary
A method and an apparatus for generating a virtual viewpoint image by obtaining at least one input viewpoint image and warping pixels of the at least one input viewpoint image to a virtual viewpoint image coordinate system; mapping a patch to a first pixel of a plurality of pixels warped to the virtual viewpoint image coordinate system when a difference between a first depth value of the first pixel and a second depth value of a second pixel adjacent to the first pixel is less than or equal to a predetermined threshold and mapping no patch to the first pixel when the difference is greater than the predetermined threshold; and generating the virtual viewpoint image by blending the plurality of pixels and/or the patch are provided.