Image Synthesis Patch Usage Control via Error Budget
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Solution Overview
Problem
Conventional techniques for stylizing synthetic renderings of virtual objects suffer from limitations such as failure to distinguish between regions with similar colors, incorrect handling of advanced lighting effects, and distortion of high-level textural features, leading to artifacts and a synthetic appearance that decreases the fidelity of the synthesized image.
Innovation Solution
Illumination-guided example-based stylization techniques that control patch usage by fitting a curve to matching errors between source and target images, ensuring equitable patch assignment and adaptive utilization to reduce artifacts and preserve textural richness, using Light Path Expression channels to accurately transfer artistic stylization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional techniques use color information to determine stylized appearance, then the process is simple, but it fails to distinguish among different regions having similar colors
Solution Approach 1:
The patent combines multiple types of information (color, normals, illumination cues) into a composite representation for determining stylized appearance. This composite approach allows the system to distinguish between regions with similar colors by incorporating additional discriminative features beyond color alone.
2Productivity
If conventional techniques rely on normals for shading, then the computation is efficient, but it fails to correctly determine locations of advanced lighting effects
Solution Approach 1:
The patent segments the lighting analysis into multiple components: basic normal-based shading for efficiency, and separate illumination cue detection for advanced lighting effects. This segmentation allows the system to maintain computational efficiency while accurately identifying shadows, highlights, and other complex lighting phenomena.
3Productivity
If conventional techniques excessively reuse a subset of patches, then the synthesis is faster, but it creates artificial repetitions and homogeneous areas
Solution Approach 1:
The patent implements feedback mechanisms that monitor patch usage patterns during synthesis. When excessive reuse of certain patches is detected, the system adjusts subsequent patch selections to maintain diversity. This feedback loop preserves visual quality by preventing artificial repetitions while still allowing efficient synthesis through controlled patch reuse.
4Reliability
If conventional techniques enforce uniform patch usage, then the distribution is equitable, but it cannot adapt to content variations in the target image
Solution Approach 1:
The patent implements dynamic patch usage enforcement that adjusts constraints based on target image content. The system starts with uniform patch usage to ensure equitable distribution, then dynamically relaxes constraints in regions where content variations require greater adaptability. This dynamic approach maintains fairness while enabling content-specific adaptations.
Data Source
AI summary
Techniques for controlling patch-usage in image synthesis are described. In implementations, a curve is fitted to a set of sorted matching errors that correspond to potential source-to-target patch assignments between a source image and a target image. Then, an error budget is determined using the curve. In an example, the error budget is usable to identify feasible patch assignments from the potential source-to-target patch assignments. Using the error budget along with uniform patch-usage enforcement, source patches from the source image are assigned to target patches in the target image. Then, at least one of the assigned source patches is assigned to an additional target patch based on the error budget. Subsequently, an image is synthesized based on the source patches assigned to the target patches.