Estimating surface reflectance properties of a complex scene under captured natural illumination (original) (raw)

Surface Reflectance Model Estimation from Daylight Illuminated Image Sequences

Procedings of the British Machine Vision Conference 1995, 1995

Accurate surface reflection models derived from existing natural scenes can be used for a variety of tasks. This paper presents a machine vision approach for determining such models. We investigate the use of simplistic models of reflection and daylight illumination to determine surface reflection properties. We attempt to determine the gloss factor of both an individual surface and a multi-faceted object when illuminated by natural light with varying sun position. Experiments are performed using synthetic image sequences of surfaces illuminated by CIE standard clear and intermediate skies, viewed from a variety of camera positions. Results show that some success can be achieved using such simple illumination models. Enhancements to the proposed method are also discussed with a view to improving system performance.

Predicting Surface Reflectance Properties of Outdoor Scenes Under Unknown Natural Illumination

ArXiv, 2021

Estimating and modelling the appearance of an object under outdoor illumination conditions is a complex process. Although there have been several studies on illumination estimation and relighting, very few of them focus on estimating the reflectance properties of outdoor objects and scenes. This paper addresses this problem and proposes a complete framework to predict surface reflectance properties of outdoor scenes under unknown natural illumination. Uniquely, we recast the problem into its two constituent components involving the BRDF incoming light and outgoing view directions: (i) surface points’ radiance captured in the images, and outgoing view directions are aggregated and encoded into reflectance maps, and (ii) a neural network trained on reflectance maps of renders of a unit sphere under arbitrary light directions infers a low-parameter reflection model representing the reflectance properties at each surface in the scene. Our model is based on a combination of phenomenologi...

Analyse de l'illumination et des propriétés de réflectance en utilisant des collections d'images

Http Www Theses Fr, 2011

The main objective of this thesis is to exploit the photometric information available in large photo collections of outdoor scenes to infer characteristics of the illumination, the objects and the cameras. To achieve this goal two problems are addressed. In a preliminary work, we explore optimal representations for the sky and compare images based on its appearance. Much of the information perceived in outdoor scenes is due to the illumination coming from the sky. The solar beams are reflected and refracted in the atmosphere, creating a global illumination ambience. In turn, this environment determines the way that we perceive objects in the real world. Given the importance of the sky as an illumination source, we formulate a generic 3-step process in order to compare images based on its appearance. These three stages are: segmentation, modeling and comparing of the sky pixels. Different approaches are adopted for the modeling and comparing phases. Performance of the algorithms is validated by finding similar images in large photo collections. A second part of the thesis aims to exploit additional geometric information in order to deduce the photometric characteristics of the scene. From a 3D structure recovered using available multi-view stereo methods, we trace back the image formation process and estimate the models for the components involved on it. Since photo collections are usually acquired with different cameras, our formulation emphasizes the estimation of the radiometric calibration for all the cameras at the same time, using a strong prior on the possible space of camera response functions. Then, in a joint estimation framework, we also propose a robust computation of the global illumination for each image, the surface albedo for the 3D structure and the radiometric calibration for all the cameras.

Recovering surface reflectance and multiple light locations and intensities from image data

Pattern Recognition Letters

We present a method to recover the reflectance of objects and the parameters of multiple lights using a 3D image acquired by a depth sensor and a stereo intensity pair. Experimental evaluation shows the ability to recover varying diffuse and constant specular reflectance parameters from object images, and simultaneously the locations and intensities of up to three distinct light sources.

Reflectance and texture of real-world surfaces

ACM Transactions on Graphics, 1999

In this work, we investigate the visual appearance of real-world surfaces and the dependence of appearance on the geometry of imaging conditions. We discuss a new texture representation called the BTF (bidirectional texture function) which captures the variation in texture with illumination and viewing direction. We present a BTF database with image textures from over 60 different samples, each observed with over 200 different combinations of viewing and illumination directions. We describe the methods involved in collecting the database as well as the importqance and uniqueness of this database for computer graphics. A related quantity to the BTF is the familiar BRDF (bidirectional reflectance distribution function). The measurement methods involved in the BTF database are conducive to simultaneous measurement of the BRDF. Accordingly, we also present a BRDF database with reflectance measurements for over 60 different samples, each observed with over 200 different combinations of v...

Recovery of Surface Reflectances Using Video Camera Image Signals under Unknown Illuminations

Optical Review, 1997

Estimation of surface spectral reflectance functions and colorimetric values 0L object colors was carried out for the irnage data captured by video camera under unknown illuminations. The estimation method is based on the finite-dimensional linear model of illuminants and surfaces using a single reference reflectance with known surLace spectral reflectance in a scene. Experimental results showed that recovered surface spectral refiectance functions are the almost same for different illuminations. This method is useful for the colorimetric calibration 0L the devices, since any set of orthonormal basis vectors to represent illuminations and any set of eigen vectors derived Lrom principal component analysis on the data set of a color chart to express surfaces of different objects can be applied to the estimation. The recovered surface reflectances were evaluated by color differences in CIE L*a*b* color space.

Acquiring and Using Realistic Reflectance Data in Computer Graphics Images

Analytical models of light reflection are in common use in computer graphics. However, as the sophistication of rendering methods has increased, analytical models have become less adequate for generating images. Reflectance data obtained by empirically measuring real world surfaces is needed to create more realistic looking images. In this paper we examine several issues relevant to using measured reflectance functions in generating computer graphics images. We give an overview of the techniques involved in measuring and tabulating reflectance data. We compare and contrast measured reflectance functions with analytical illumination models, and evaluate several methods for interpolating tabulated reflectance functions. We also highlight potential areas of future research. 1 Introduction The most fundamental operation in rendering computer graphics images is the computation of how light reflects off surfaces. This computation is often performed using a local illumination model. This i...

Recovery of Surface Normals and Reflectance from Different Lighting Conditions

Lecture Notes in Computer Science, 2008

This paper presents a method for finding the surface normals and reflectance of an object from a set of images obtained under different lighting conditions. This set of images, assuming a Lambertian object, can be approximated by a three dimensional linear subspace, under an orthographic camera model and without shadows and specularities. However, a higher dimensional subspace is needed when images present pixels in shadow, specularities or ambient illumination. This paper proposes on the one hand to consider pixels in shadow and specularities as missing data; and on the other hand a rank-four formulation to recover the ambient illumination. An adaptation of the Alternation technique is introduced to compute the sought surface normals and light-source matrices. Experimental results show the good performance of the proposed Alternation-based strategy.

Image statistics for surface reflectance perception

Journal of the Optical Society of America A, 2008

Human observers can distinguish the albedo of real-world surfaces even when the surfaces are viewed in isolation, contrary to the Gelb effect. We sought to measure this ability and to understand the cues that might underlie it. We took photographs of complex surfaces such as stucco and asked observers to judge their diffuse reflectance by comparing them to a physical Munsell scale. Their judgments, while imperfect, were highly correlated with the true reflectance. The judgments were also highly correlated with certain image statistics, such as moment and percentile statistics of the luminance and subband histograms. When we digitally manipulated these statistics in an image, human judgments were correspondingly altered. Moreover, linear combinations of such statistics allow a machine vision system (operating within the constrained world of single surfaces) to estimate albedo with an accuracy similar to that of human observers. Taken together, these results indicate that some simple image statistics have a strong influence on the judgment of surface reflectance.