Photometric method for determining surface orientation from multiple images
Shape from shading
Height and gradient from shading
International Journal of Computer Vision
Estimation of Illuminant Direction, Albedo, and Shape from Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parametric Shape-from-Shading by Radial Basis Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Radiometry of Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Camera Self-Calibration: Theory and Experiments
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Shadow Graphs and Surface Reconstruction
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
On 3-D Surface Reconstruction Using Shape from Shadows
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
In defence of the 8-point algorithm
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Enhanced 3D Shape Recovery Using the Neural-Based Hybrid Reflectance Model
Neural Computation
Learning shape from shading by a multilayer network
IEEE Transactions on Neural Networks
A neural network scheme for transparent surface modelling
GRAPHITE '05 Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Depth estimation of face images based on the constrained ICA model
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
Linear-nonlinear neuronal model for shape from shading
Pattern Recognition Letters
A neural network for simultaneously reconstructing transparent and opaque surfaces
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
A study of a soft computing based method for 3D scenario reconstruction
Applied Soft Computing
GPGPU implementation of growing neural gas: Application to 3D scene reconstruction
Journal of Parallel and Distributed Computing
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In this paper, we present a new neural network (NN) for three-dimensional (3D) shape reconstruction. This NN provides an analytic mapping of an initial 3D polyhedral model into its projection depth images. Through this analytic mapping, the NN can analytically refine vertices position of the model using error back-propagation learning. This learning is based on shape-from-shading (SFS) depth maps taken from multiple views. The depth maps are obtained by Tsai-Shah SFS algorithm. They are considered as partial 3D shapes of the object to be reconstructed. The task is to reconstruct an accurate and complete representation of a given object relying only on a limited number of views and erroneous SFS depth maps. Through hierarchical reconstruction and annealing reinforcement strategies, our reconstruction system gives more exact and stable results. In addition, it corrects and smoothly fuses the erroneous SFS depth maps. The implementation of this neural network algorithm used in this paper is available at http://kumazawa-www.cs.titech.ac.jp/~fanany/MV-SPRNN/mv-sprnn.html.