Showing papers by "William A. P. Smith published in 2011"

Shape-from-shading under complex natural illumination

Abstract: We present a shape-from-shading algorithm for Lambertian surfaces of uniform but unknown albedo, illuminated by unknown, arbitrarily complex environment lighting. Our approach is based on a first order spherical harmonic approximation to the reflectance map. This is estimated from the image using surface normals interpolated from boundary points. The shape-from-shading step minimises local brightness error and an edge sensitive smoothness constraint. This involves the solution of a linear least squares problem with a quadratic equality constraint, the global optimum of which can be found using the method of Lagrange multipliers. We demonstrate the performance of the algorithm on complex objects rendered under realworld illumination.

Inverse Rendering with a Morphable Model: A Multilinear Approach.

Abstract: In this paper, we present a complete framework to inverse render faces from single images using a 3D Morphable Model (3DMM). A 3DMM is a linear statistical model of 3D shape and texture [2]. In general, inverse rendering of faces from single photographs is ill-posed, as the same appearance can be obtained by different underlaying factors. For instance, a red pixel can be caused by skin colour, red illumination, or an increased camera sensitivity in the red channel. A combination of these factors is also possible. For an object of known shape under complex natural illumination, the well known work of Ramamoorthi [4] shows how the spherical harmonic domain can be used to estimate one or more of: illumination, surface texture and reflectance properties. We revisit this classical formulation in the context of 3DMMs. Previous methods for fitting a 3DMM based on analysis-by-synthesis recover all parameters in a single, nonconvex objective function [2, 3]. To reduce the threat of getting stuck in local minima, Romdhani introduced a fitting algorithm which incorporates features like edges and specular highlights into the cost function [5]. These fitting algorithms make limited assumptions about the illumination environment and only model ambient light and one directional light source. Zhang and Samaras [6] used spherical harmonics to model unconstrained illumination, although at the cost of assuming a simple Lambertian reflectance model.

DL_POLY_2 adaptations for solvation studies

Abstract: Adaptations of the molecular dynamics engine DL_POLY_2 were recently made to facilitate the investigation of questions arising mainly in the study of solvation dynamics. This paper presents the new facilities, with consideration of practical points for their efficient use and illustrative results obtained with them. Supplementary Information provides further details of their implementation to encourage future improvements and extensions. The adaptations of DL_POLY_2 for solvation studies are: • Species by species and inter-species breakdown of the total energy for systems containing several species, such as solutions or models of adsorption, with, as an illustration, diffusion of a particular water molecule in a microporous silica zeolite, silicalite. The new facilities allow correlation of the trajectory of the molecule with its interaction with the host matrix. • Solvation-induced spectral shifts, illustrated by the absorption shift and Stokes shift of a cyanoaromatic dye in solution in methanol. We dis...

Simplification of 3D morphable models

Abstract: In this paper we show how to simplify a 3D morphable model. Our method only requires knowledge of the original highest resolution statistical model and leads to low resolution models in which the model statistics are a subset of the original high resolution model. We employ an iterative edge collapse strategy, where the deleted edge is chosen as a function of the model statistics. We show that the expected value of the Quadric Error Metric can be computed in closed form for a PCA deformable model. Model parameters obtained using the model at any resolution (lower) can be used to reconstruct a high resolution surface, providing a route to super-resolution. We provide experimental results for a statistical face model, showing how the simplified models improve the efficiency of model fitting. We are able to decrease the model resolution and fitting time by factors of approximately 10 and 4 respectively whilst inducing an error which is only slightly larger than the fitting error of the original model.

Inverse rendering in SUV space with a linear texture model

Abstract: In this paper, we consider the problem of inverse rendering in the case where surface texture can be approximated by a linear basis. Assuming a dichromatic reflectance model, we show that spherical harmonic illumination coefficients and texture parameters can be estimated in a specular invariant colour subspace by solving a system of bilinear equations. We focus on the case of faces, where both shape and texture can be efficiently described by a linear statistical model. In this context, we are able to fit a 3D morphable model to a single colour image, accounting for both non-Lambertian specular reflectance and complex illumination of the same light source colour. We are able to recover statistical texture model parameters with an accuracy comparable to more computationally expensive analysis-by-synthesis approaches. Moreover, our approach requires only the solution of convex optimisation problems.

A computer simulation study of the interaction between passivated and bare gold nanoclusters

Abstract: Molecular dynamics simulations have been performed with the objective of understanding the phenomenon of nanoparticle aggregation. We have attempted to calculate the free energy associated with the interaction between two 38-atom gold nanocores, with attached passivating thiol chains, in a supercritical ethane solvent and in the vacuum, and without passivating chains in ethane at the critical density and twice the critical density. Our model differs from those used by others in that each gold nanocore is bound by a realistic metal potential that is not formally rigid. In the case of the passivated nanoparticles, we observe profound structural changes in the nanocores, which radically affect the nature of the interaction between them—to the extent that fusion of the two gold nanocores cannot be prevented under the conditions examined. Bare nanocores, on the other hand, do not exhibit much structural change until close contact occurs. The fused nanocores in the passivated and bare nanocore systems have significantly different morphologies. There is evidence that at higher solvent density, the interaction between bare nanocores is slightly repulsive.

Facial expression recognition using nonrigid motion parameters and shape-from-shading

Abstract: This paper presents a 3D motion based approach to facial expression recognition from video sequences. A non-Lambertian shapefrom-shading (SFS) framework is used to recover 3D facial surfaces. The SFS technique avoids heavy computational requirements normally encountered by using a 3D face model. Then, a parametric motion model and optical flow are employed to obtain the nonrigid motion parameters of surface patches. At first, we obtain uniform motion parameters under the assumptions that motion due to change in expressions is temporally consistent. Then we relax the uniform motion constraint, and obtain temporal motion parameters. The two types of motion parameters are used to train and classify using Adaboost and HMM-based classifier. Experimental results show that temporal motion parameters perform much better than uniform motion parameters, and can be used to efficiently recognize facial expression.

Combining probabilistic shape-from-shading and statistical facial shape models

Abstract: Shape-from-shading is an interesting approach to the problem of finding the shape of a face because it only requires one image and no subject participation. However, SfS is not accurate enough to produce good shape models. Previously, SfS has been combined with shape models to produce realistic face reconstructions. In this work, we aim to improve the quality of such models by exploiting a probabilistic SfS model based on Fisher-Bingham 8-parameter distributions (FB8). The benefits are two-fold; firstly we can correctly weight the contributions of the data and model where the surface normals are uncertain, and secondly we can locate areas of shadow and facial hair using inconsistencies between the data and model. We sample the FB8 distributions using a Gibbs sampling algorithm. These are then modelled as Gaussian distributions on the surface tangent plane defined by the model. The shape model provides a second Gaussian distribution describing the likely configurations of the model; these distributions are combined on the tangent plane of the directional sphere to give the most probable surface normal directions for all pixels. The Fisher criterion is used to locate inconsistencies between the two distributions and smoothing is used to deal with outliers originating in the shadowed and specular regions. A surface height model is then used to recover surface heights from surface normals. The combined approach shows improved results over the case when only surface normals from shape-from-shading are used.