31 research outputs found
Analysis and approximation of some Shape-from-Shading models for non-Lambertian surfaces
The reconstruction of a 3D object or a scene is a classical inverse problem
in Computer Vision. In the case of a single image this is called the
Shape-from-Shading (SfS) problem and it is known to be ill-posed even in a
simplified version like the vertical light source case. A huge number of works
deals with the orthographic SfS problem based on the Lambertian reflectance
model, the most common and simplest model which leads to an eikonal type
equation when the light source is on the vertical axis. In this paper we want
to study non-Lambertian models since they are more realistic and suitable
whenever one has to deal with different kind of surfaces, rough or specular. We
will present a unified mathematical formulation of some popular orthographic
non-Lambertian models, considering vertical and oblique light directions as
well as different viewer positions. These models lead to more complex
stationary nonlinear partial differential equations of Hamilton-Jacobi type
which can be regarded as the generalization of the classical eikonal equation
corresponding to the Lambertian case. However, all the equations corresponding
to the models considered here (Oren-Nayar and Phong) have a similar structure
so we can look for weak solutions to this class in the viscosity solution
framework. Via this unified approach, we are able to develop a semi-Lagrangian
approximation scheme for the Oren-Nayar and the Phong model and to prove a
general convergence result. Numerical simulations on synthetic and real images
will illustrate the effectiveness of this approach and the main features of the
scheme, also comparing the results with previous results in the literature.Comment: Accepted version to Journal of Mathematical Imaging and Vision, 57
page
A discrete Hughes' model for pedestrian flow on graphs
In this paper, we introduce a discrete time-finite state model for pedestrian
flow on a graph in the spirit of the Hughes dynamic continuum model. The
pedestrians, represented by a density function, move on the graph choosing a
route to minimize the instantaneous travel cost to the destination. The density
is governed by a conservation law while the minimization principle is described
by a graph eikonal equation. We show that the model is well posed and we
implement some numerical examples to demonstrate the validity of the proposed
model
A High-Order Scheme for Image Segmentation via a modified Level-Set method
In this paper we propose a high-order accurate scheme for image segmentation
based on the level-set method. In this approach, the curve evolution is
described as the 0-level set of a representation function but we modify the
velocity that drives the curve to the boundary of the object in order to obtain
a new velocity with additional properties that are extremely useful to develop
a more stable high-order approximation with a small additional cost. The
approximation scheme proposed here is the first 2D version of an adaptive
"filtered" scheme recently introduced and analyzed by the authors in 1D. This
approach is interesting since the implementation of the filtered scheme is
rather efficient and easy. The scheme combines two building blocks (a monotone
scheme and a high-order scheme) via a filter function and smoothness indicators
that allow to detect the regularity of the approximate solution adapting the
scheme in an automatic way. Some numerical tests on synthetic and real images
confirm the accuracy of the proposed method and the advantages given by the new
velocity.Comment: Accepted version for publication in SIAM Journal on Imaging Sciences,
86 figure
Shape Optimization for Thermal Insulation Problems
[EN] In this work we consider two domains: an external domain whose geometry varies,
and an internal fixed one. From the thermal insulation viewpoint, we are considering a body
to be insulated, enveloped in a layer of insulator, and we want to find the best shape for the
thermal insulator, in terms of heat dispersion. Mathematically, our problem is described by an
elliptic partial differential equation with Dirichlet-Robin boundary conditions.This research has been carried on within the PON R&I 2014-2020 - “AIM: Attraction and International Mobility” (Linea 2.1, project AIM1834118 - 2, CUP: E61G19000050001). The authors are members of the INdAM Research Group GNCS.Tozza, S.; Toraldo, G. (2022). Shape Optimization for Thermal Insulation Problems. En Proceedings of the YIC 2021 - VI ECCOMAS Young Investigators Conference. Editorial Universitat Politècnica de València. 11-15. https://doi.org/10.4995/YIC2021.2021.12288OCS111
A unified approach to the well-posedness of some non-Lambertian models in Shape-from-Shading theory
In this paper we show that the introduction of an attenuation factor in the
%image irradiance brightness equations relative to various perspective Shape
from Shading models allows to make the corresponding differential problems
well-posed. We propose a unified approach based on the theory of viscosity
solution and we show that the brightness equations with the attenuation term
admit a unique viscosity solution. We also discuss in detail the possible
boundary conditions that we can use for the Hamilton-Jacobi equations
associated to these models
An overview of some mathematical techniques and problems linking 3D vision to 3D printing
Computer Vision and 3D printing have rapidly evolved in the last 10 years but
interactions among them have been very limited so far, despite the fact that
they share several mathematical techniques. We try to fill the gap presenting
an overview of some techniques for Shape-from-Shading problems as well as for
3D printing with an emphasis on the approaches based on nonlinear partial
differential equations and optimization. We also sketch possible couplings to
complete the process of object manufacturing starting from one or more images
of the object and ending with its final 3D print. We will give some practical
examples of this procedure
Linear Differential Constraints for Photo-polarimetric Height Estimation
In this paper we present a differential approach to photo-polarimetric shape
estimation. We propose several alternative differential constraints based on
polarisation and photometric shading information and show how to express them
in a unified partial differential system. Our method uses the image ratios
technique to combine shading and polarisation information in order to directly
reconstruct surface height, without first computing surface normal vectors.
Moreover, we are able to remove the non-linearities so that the problem reduces
to solving a linear differential problem. We also introduce a new method for
estimating a polarisation image from multichannel data and, finally, we show it
is possible to estimate the illumination directions in a two source setup,
extending the method into an uncalibrated scenario. From a numerical point of
view, we use a least-squares formulation of the discrete version of the
problem. To the best of our knowledge, this is the first work to consider a
unified differential approach to solve photo-polarimetric shape estimation
directly for height. Numerical results on synthetic and real-world data confirm
the effectiveness of our proposed method.Comment: To appear at International Conference on Computer Vision (ICCV),
Venice, Italy, October 22-29, 201
Linear Depth Estimation from an Uncalibrated, Monocular Polarisation Image
We present a method for estimating surface height directly from a single polarisation image simply by solving a large, sparse system of linear equations. To do so, we show how to express polarisation constraints as equations that are linear in the unknown depth. The ambiguity in the surface normal azimuth angle is resolved globally when the optimal surface height is reconstructed. Our method is applicable to objects with uniform albedo exhibiting diffuse and specular reflectance. We extend it to an uncalibrated scenario by demonstrating that the illumination (point source or first/second order spherical harmonics) can be estimated from the polarisation image, up to a binary convex/concave ambiguity. We believe that our method is the first monocular, passive shape-from-x technique that enables well-posed depth estimation with only a single, uncalibrated illumination condition. We present results on glossy objects, including in uncontrolled, outdoor illumination
Linear Differential Constraints for Photo-polarimetric Height Estimation
In this paper we present a differential approach to photopolarimetric shape estimation. We propose several alternative differential constraints based on polarisation and photometric shading information and show how to express them in a unified partial differential system. Our method uses the image ratios technique to combine shading and polarisation information in order to directly reconstruct surface height, without first computing surface normal vectors. Moreover, we are able to remove the non-linearities so that the problem reduces to solving a linear differential problem. We also introduce a new method for estimating a polarisation image from multichannel data and, finally, we show it is possible to estimate the illumination directions in a two source setup, extending the method into an uncalibrated scenario. From a numerical point of view, we use a least-squares formulation of the discrete version of the problem. To the best of our knowledge, this is the first work to consider a unified differential approach to solve photo-polarimetric shape estimation directly for height. Numerical results on synthetic and real-world data confirm the effectiveness of our proposed method
Height-from-Polarisation with Unknown Lighting or Albedo
We present a method for estimating surface height directly from a single polarisation image simply by solving a large, sparse system of linear equations. To do so, we show how to express polarisation constraints as equations that are linear in the unknown height. The local ambiguity in the surface normal azimuth angle is resolved globally when the optimal surface height is reconstructed. Our method is applicable to dielectric objects exhibiting diffuse and specular reflectance, though lighting and albedo must be known. We relax this requirement by showing that either spatially varying albedo or illumination can be estimated from the polarisation image alone using nonlinear methods. In the case of illumination, the estimate can only be made up to a binary ambiguity which we show is a generalised Bas-relief transformation corresponding to the convex/concave ambiguity. We believe that our method is the first passive, monocular shape-from-x technique that enables well-posed height estimation with only a single, uncalibrated illumination condition. We present results on real world data, including in uncontrolled, outdoor illumination