3D Face Model Illumination Basis Calculation

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Solution Overview

Problem

Conventional 3-dimensional shape estimation systems require manual input of illumination parameters, leading to a heavy user burden and increased processing time due to nonlinear relationships between luminance values and illumination parameters, and involve complex calculations for shade and shadow generation, resulting in local solution issues and prolonged processing times.

Innovation Solution

An image processing system that calculates an individual illumination basis using spherical harmonics based on 3-dimensional shape and texture data, allowing for image reproduction under various illumination conditions without initial parameter input, and employs a linear illumination model to simplify calculations and avoid local solutions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If manual input of illumination parameters is required, then the system can handle various illumination conditions, but the user burden increases and processing time increases

Engineering Contradiction:

Improveillumination condition handlingVSAvoiduser input requirement

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system automatically estimates illumination parameters by analyzing the relationship between luminance values and illumination parameters in the input image, eliminating the need for manual user input while maintaining accurate handling of various illumination conditions

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-calculates and stores correspondence relationships between luminance values and illumination parameters, allowing automatic illumination parameter estimation during image processing without requiring real-time manual input

Inventive Principle:

Principle #10Preliminary action

2Reliability

If nonlinear optimization is used to estimate illumination parameters, then the system can handle complex illumination relationships, but processing time increases and local solutions may occur

Engineering Contradiction:

Improveillumination parameter estimation accuracyVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system changes the approach from nonlinear optimization to linear estimation by using pre-stored correspondence relationships between luminance values and illumination parameters, transforming the complex nonlinear problem into a simpler linear calculation that avoids local solutions and reduces processing time

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system replaces the complex nonlinear optimization mechanism with a linear estimation mechanism based on pre-established correspondence relationships, simplifying the computational process while maintaining estimation accuracy

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Manufacturing precision

If complex shade and shadow generation calculations are performed, then the image quality improves, but processing time increases

Engineering Contradiction:

Improveimage qualityVSAvoidprocessing speed

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The system pre-calculates and stores correspondence relationships between luminance values and illumination parameters, allowing fast linear estimation during actual image processing without performing complex real-time calculations

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system replaces complex nonlinear optimization and iterative calculations with simple linear estimation based on pre-stored data, dramatically reducing processing time while maintaining image quality

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach reduces user input requirements, speeds up processing by eliminating the need for nonlinear optimization, and enhances accuracy by avoiding local solutions, enabling faster and more precise estimation of 3-dimensional shapes and textures.

Implementation Method 1

calculates an individual illumination basis using spherical harmonics based on 3-dimensional shape and texture data

Methodology Applied

Scientific EffectSpherical harmonics:

Data Source

PatentUS8320660B2Image processing system, 3-dimensional shape estimation system, object position/posture estimation system and image generation system

Publication Date: 2012.11.27 NEC CORP

AI summary

An object of the present invention is to process an image without a need to previously find out the initial value of a parameter representing an illumination condition and without a need for a user to manually input the illumination parameter. An image processing system includes a generalized illumination basis model generation means 300, a position/posture initial value input means 102, a face model generation means 103, an illumination basis model calculation means 301, a perspective transformation means 202, an illumination correction means 203, and a parameter update means 204. The generalized illumination basis model generation means 300 previously calculates a generalized illumination basis model. The face model generation means 103 generates an individual 3-dimensional shape and texture from the generalized 3-dimensional face model. The illumination basis model calculation means 301 generates an individual illumination basis from the generalized illumination basis model using the same parameter. The parameter update means 204 searches for a parameter of a shape, texture, and position/posture to minimize the error when the input image is reproduced.