Depth-of-field blur generation via depth map and aperture control
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Solution Overview
Problem
Conventional digital effect generation systems are inefficient and imprecise in applying depth-of-field blur effects to digital images, lacking control over focal depth and blur intensity, and often result in inconsistent and unintended blur effects, especially at depth discontinuities.
Innovation Solution
A digital effect generation system that receives user inputs for focal depth and aperture values, generates a depth map, and applies depth-of-field blur effects to down-sampled images, allowing for precise control over the blur effect through a combination of down-sampling, depth map generation, and up-sampling processes, while minimizing focal loss at object boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ray tracing and real camera models are used to generate depth-of-field blur effects, then accuracy is improved, but processing time increases significantly
Solution Approach 1:
The patent uses a depth map as a simplified copy or representation of the actual scene depth information, rather than performing computationally intensive ray tracing. The depth map captures essential depth relationships in a condensed format that can be processed efficiently while still enabling accurate depth-of-field blur effects.
Solution Approach 2:
The patent transforms the complex ray tracing problem into a more efficient parameter-based approach by using depth map values and aperture parameters to control the blur effect. This changes the computational parameters from ray-based geometric calculations to simpler depth-value-based calculations that achieve similar visual results with much lower computational cost.
2Productivity
If conventional blur algorithms are used to improve processing speed, then efficiency is improved, but accuracy deteriorates with inconsistent and unintended blur effects
Solution Approach 1:
The depth map serves as an efficient intermediate representation that enables conventional processing speeds while maintaining accuracy. By copying depth information into a simplified map structure, the system achieves both speed and consistency in blur effect application.
Solution Approach 2:
The patent replaces complex mechanical/optical simulation (ray tracing) with a computational substitution using depth maps and aperture parameters. This substitution maintains the essential physics of depth-of-field effects while using simpler mathematical operations that are both fast and consistent.
3Adaptability or versatility
If single-lens reflex cameras are used to generate depth-of-field blur effects, then blur effect capability is provided, but device complexity and cost increase
Solution Approach 1:
The patent creates a digital copy of the depth information through depth map generation, eliminating the need for complex physical camera systems. The depth map captures the essential depth relationships that would otherwise require sophisticated optical hardware to achieve.
Solution Approach 2:
The patent substitutes physical camera optics (lenses, apertures, focal mechanisms) with computational methods using depth maps and aperture parameters. This replacement achieves the same depth-of-field visual effects through software-based image processing rather than mechanical-optical systems.
4Adaptability or versatility
If large aperture lenses are used to increase blur effect intensity, then blur intensity control is improved, but precision deteriorates with imprecise blur application
Solution Approach 1:
The patent uses aperture parameters as a controlled variable to adjust blur intensity in a precise and predictable manner. By changing this parameter within the computational model, users can achieve different levels of blur effect with exact control over the resulting appearance, unlike the less predictable behavior of physical lens aperture changes.
Data Source
AI summary
Techniques of generating depth-of-field blur effects on digital images by digital effect generation system of a computing device are described. The digital effect generation system is configured to generate depth-of-field blur effects on objects based on focal depth value that defines a depth plane in the digital image and a aperture value that defines an intensity of blur effect applied to the digital image. The digital effect generation system is also configured to improve the accuracy with which depth-of-field blur effects are generated by performing up-sampling operations and implementing a unique focal loss algorithm that minimizes the focal loss within digital images effectively.