The variational approach to shape from shading
Computer Vision, Graphics, and Image Processing
Numerical shape from shading and occluding boundaries
Shape from shading
CVGIP: Image Understanding
Estimation of Illuminant Direction, Albedo, and Shape from Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Tracking level sets by level sets: a method for solving the shape from shading problem
Computer Vision and Image Understanding
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
New Constraints on Data-Closeness and Needle Map Consistency for Shape-from-Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiresolution Approach for Shape from Shading Coupling Deterministic and Stochastic Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering Facial Shape Using a Statistical Model of Surface Normal Direction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstruction of 3D Face from a Single 2D Image for Face Recognition
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
Efficient 3D reconstruction for face recognition
Pattern Recognition
What is the range of surface reconstructions from a gradient field?
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Integrated Computer-Aided Engineering
A soft computing method for detecting lifetime building thermal insulation failures
Integrated Computer-Aided Engineering
Multi-object segmentation approach based on topological derivative and level set method
Integrated Computer-Aided Engineering
Improvement of surface roughness models for face milling operations through dimensionality reduction
Integrated Computer-Aided Engineering
Improving fusion with optimal weight selection in Face Recognition
Integrated Computer-Aided Engineering
Reconstruction of occluded facial images using asymmetrical Principal Component Analysis
Integrated Computer-Aided Engineering
2D and 3D palmprint information, PCA and HMM for an improved person recognition performance
Integrated Computer-Aided Engineering
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We propose a novel method for 3D head reconstruction and view-invariant recognition from single 2D images. We employ a deterministic Shape From Shading (SFS) method with initial conditions estimated by Hybrid Principal Component Analysis (HPCA) and multi-level global optimization with error-dependent smoothness and integrability constraints. Our HPCA algorithm provides good initial estimates of 3D range mapping for the SFS optimization and yields much improved 3D head reconstruction. The paper also presents novel approaches to global optimization. It also describes a novel method in SFS handling of variable and unknown surface albedo, a problem with unsatisfactory solutions by prevalent SFS methods. In the experiments, we reconstruct 3D head range images from 2D single images in different views. The 3D reconstructions are then used to recognize stored model persons. This enables one to recognize faces in wide range of views. Empirical results show that our HPCA based SFS method provides 3D head reconstructions that notably improve the accuracy compared to other approaches. 3D reconstructions derived from images of 40 persons are tested against 80 3D head models and a recognition rate of over 90% is achieved. Such a capability was not demonstrated by any other method for view-invariant face recognition.