Some illumination models for industrial applications of photometric stereo (original) (raw)

LED-Based Photometric Stereo: Modeling, Calibration and Numerical Solution

Journal of Mathematical Imaging and Vision, 2017

We conduct a thorough study of photometric stereo under nearby point light source illumination, from modeling to numerical solution, through calibration. In the classical formulation of photometric stereo, the luminous fluxes are assumed to be directional, which is very difficult to achieve in practice. Rather, we use light-emitting diodes (LEDs) to illuminate the scene to be reconstructed. Such point light sources are very convenient to use, yet they yield a more complex photometric stereo model which is arduous to solve. We first derive in a physically sound manner this model, and show how to calibrate its parameters. Then, we discuss two state-of-the-art numerical solutions. The first

Photometric stereo: Lambertian reflectance and light sources with unknown direction and strength

This paper reconsiders the familiar case of photometric stereo under the assumption of Lambertian surface re ectance and three distant point sources of illumination. Here, it is assumed that the directions to and the relative strengths of the three light sources are not known a priori. Rather, estimation of these parameters becomes part of the problem formulation. Each light source is represented by a 3-D vector that points in the direction of the light source and has magnitude proportional to the strength of the light source. Thus, nine parameters are required to characterize the three light sources. It is shown that, regardless of object shape, triples of measured intensity values are constrained to lie on a quadratic surface having six degrees of freedom. Estimation of the six parameters of the quadratic surface allows the determination of the nine parameters of the light sources up to an unknown rotation. This is su cient to determine object shape, although attitude with respect to the world-based or the camera-based coordinate system can not be simultaneously recovered without additional information.

Photometric Stereo with General, Unknown Lighting

International Journal of Computer Vision, 2006

Work on photometric stereo has shown how to recover the shape and reflectance properties of an object using multiple images taken with a fixed viewpoint and variable lighting conditions. This work has primarily relied on the presence of a single point source of light in each image. In this paper we show how to perform photometric stereo assuming that all lights in a scene are isotropic and distant from the object but otherwise unconstrained. Lighting in each image may be an unknown and arbitrary combination of diffuse, point and extended sources. Our work is based on recent results showing that for Lambertian objects, general lighting conditions can be represented using low order spherical harmonics. Using this representation we can recover shape by performing a simple optimization in a low-dimensional space. We also analyze the shape ambiguities that arise in such a representation.

Practical 3D Reconstruction Based on Photometric Stereo

Studies in Computational Intelligence, 2010

Photometric Stereo is a powerful image based 3d reconstruction technique that has recently been used to obtain very high quality reconstructions. However, in its classic form, Photometric Stereo suffers from two main limitations: Firstly, one needs to obtain images of the 3d scene under multiple different illuminations. As a result the 3d scene needs to remain static during illumination changes, which prohibits the reconstruction of deforming objects. Secondly, the images obtained must be from a single viewpoint. This leads to depth-map based 2.5 reconstructions, instead of full 3d surfaces. The aim of this chapter is to show how these limitations can be alleviated, leading to the derivation of two practical 3d acquisition systems: The first one, based on the powerful Coloured Light Photometric Stereo method can be used to reconstruct moving objects such as cloth or human faces. The second, permits the complete 3d reconstruction of challenging objects such as porcelain vases. In addition to algorithmic details, the chapter pays attention to practical issues such as setup calibration, detection and correction of self and cast shadows. We provide several evaluation experiments as well as reconstruction results.

Identifying the lights position in photometric stereo under unknown lighting

2021 21st International Conference on Computational Science and Its Applications (ICCSA), 2021

Reconstructing the 3D shape of an object from a set of images is a classical problem in Computer Vision. Photometric stereo is one of the possible approaches. It stands on the assumption that the object is observed from a fixed point of view under different lighting conditions. The traditional approach requires that the position of the light sources is accurately known. It has been proved that the lights position can be estimated directly from the data when at least 6 images of the observed object are available. In this paper, we present a Matlab implementation of the algorithm for solving the photometric stereo problem under unknown lighting, and propose a simple shooting technique to solve the bas-relief ambiguity.

Sampling Light Field for Photometric Stereo

International Journal of Computer Theory and Engineering, 2013

To implement the photometric stereo technique, the radiance distribution of the respective light sources from the different illumination directions must be accurately known. Most previous work has tended to assume distance point sources, so that a collimated and uniform illumination distribution can be approximated, thereby allowing the photometric stereo problem to be easily solved in a linear way. However, there can be significant practical difficulties in realizing such idealized light sources in real world applications. In addition, the strategy of using distant light sources produces a low signal/noise ratio for the system, and is also unsuitable for applications where setup space is limited. These problems potentially limit new opportunities for the wider applications of photometric stereo beyond the research laboratory in evolving areas such as industrial inspection, security and medical applications. This paper proposes a compensation method for illumination radiance to allow the possibility of employing normal low-cost commercial light sources. A flat diffuse surface with either homogeneous or heterogeneous albedo distribution is used to sample the radiance distribution before implementing photometric stereo. The unevenly distributed light radiance is eliminated by using the acquired reference information. The experimental results demonstrate the efficacy of the proposed method.

Orthogonal Illuminations in Two Light-Source Photometric Stereo

Lecture Notes in Computer Science, 2016

In this paper we investigate the case of ambiguous shape reconstruction from two light-source photometric stereo based on illuminating the unknown Lambertian surface. So-far this problem is merely well-understood for two linearly independent light-source directions with one illumination assumed as overhead. As already established, a necessary and sufficient condition to disambiguate the entire shape reconstruction process is controlled by the satisfaction of the corresponding secondorder linear PDE with constant coefficients in two independent variables. This work extends the latter to an arbitrary pair of light-source directions transforming the above constraint into a special nonlinear PDE. In addition, a similar ambiguity analysis is also performed for a special configuration of two light-source directions assumed this time as orthogonal and contained in the vertical plane. Finally, this work is supplemented by illustrative examples exploiting symbolic computation used within a framework of continuous reflectance map model (i.e. an image irradiance equation) and applied to a genuine Lambertian surfaces.

Exploration of Photometric Stereo Technology Applies to 3D Model Reconstruction

International journal of engineering research and technology, 2013

An efficient method has been presented to achieve an accurate dense 3D reconstruction of objects using photometric stereo technology. The task of recovering three-dimensional geometry from two dimensional views of a scene is called 3D reconstruction. Photometric Stereo is a powerful image based 3D reconstruction technique that has recently been used to obtain very high quality reconstructions. The Photometric Stereo (PS) technique uses several images of the same surface taken from the same viewpoint but under illuminations with different directions. The illumination conditions refer to the light source direction and intensity, and reflectance properties mean what type of surface is under consideration i.e. Lambertian or non-Lambertian. . The algorithm has been tested on synthetic as well as real datasets and very encouraging results have been obtained.

A hand-held photometric stereo camera for 3-D modeling

2009 IEEE 12th International Conference on Computer Vision, 2009

This paper presents a simple yet practical 3-D modeling method for recovering surface shape and reflectance from a set of images. We attach a point light source to a hand-held camera to add a photometric constraint to the multi-view stereo problem. Using the photometric constraint, we simultaneously solve for shape, surface normal, and reflectance. Unlike prior approaches, we formulate the problem using realistic assumptions of a near light source, non-Lambertian surfaces, perspective camera model, and the presence of ambient lighting. The effectiveness of the proposed method is verified using simulated and real-world scenes.

Ascertaining the Ideality of Photometric Stereo Datasets under Unknown Lighting

Algorithms

The standard photometric stereo model makes several assumptions that are rarely verified in experimental datasets. In particular, the observed object should behave as a Lambertian reflector, and the light sources should be positioned at an infinite distance from it, along a known direction. Even when Lambert’s law is approximately fulfilled, an accurate assessment of the relative position between the light source and the target is often unavailable in real situations. The Hayakawa procedure is a computational method for estimating such information directly from data images. It occasionally breaks down when some of the available images excessively deviate from ideality. This is generally due to observing a non-Lambertian surface, or illuminating it from a close distance, or both. Indeed, in narrow shooting scenarios, typical, e.g., of archaeological excavation sites, it is impossible to position a flashlight at a sufficient distance from the observed surface. It is then necessary to ...