An Investigation of Object Shadows Utilization In 3D Shape Re-Construction Using Inexpensive Equipment

An approach for automatic 3D object re-construction using its shadow ispresented. The approach investigates the use of information inherited by thegenerated object shadows to re-construct the object geometry. An algorithm isdeveloped that make use of object height information for the directions associatedwith the incident light and the generated object shadows, hence, acquired heightfeatures represents the object features that have actually obstructed the incidentlight. The technique is tested using objects of different shapes. Close to realmeasurements are gained and the overall accuracy of the system is found to bewithin 0.75 mm using the adopted imaging hardware and setup. Obtained resultsconfirmed the validity of the proposed approach

Flat Bidirectional Texture Functions

Highly-realistic materials in computer graphics are computationally and memory demanding. Currently, the most versatile techniques are based on Bidirectional Texture Functions (BTFs), an image-based approximation of appearance. Extremely realistic images may be quickly obtained with BTFs at the price of a huge amount of data. Even though a lot of BTF compression schemes have been introduced during the last years, the main remaining challenge arises from the fact that a BTF embeds many different optical phenomena generated by the underlying meso-geometry (parallax effects, masking, shadow casting, inter-reflections, etc.). We introduce a new representation for BTFs that isolates parallax effects. On one hand, we built a flattened BTF according to a global spatial parameterization of the underlying meso-geometry. On the other hand, we generate a set of view-dependent indirection maps on this spatial parameterization to encode all the parallax effects. We further analyze this representation on a various set of synthetic BTF data to show its benefits on view-dependent coherency, and to find the best sampling strategy. We also demonstrate that this representation is well suited for hardware acceleration on current GPUs.En Infographie, les matériaux hautement réalistes sont grand consommateurs de puissance de calculs ainsi que de mémoire. A l'heure actuelle, les techniques les plus versatiles reposent sur les fonctions de textures bidirectionnelles (BTFs) représentant une approximation à partir d'images de l'apparence des matériaux. Des images extrêmement réalistes peuvent être obtenues rapidement à l'aide de BTFs au prix d'une énorme quantité de données. Bien que de nombreux schémas de compression de BTFs aient été introduits au cours de ces dernières années, le principal challenge restant provient du fait qu'une BTF mélange différents phénomènes optiques générés par la meso-géométrie sous-jacente (effets de parallaxe ou de masquage, ombres portées, inter-réflexions, etc.), effets qui ne peuvent être que correctement gérés à l'aide d'approches appropriées. Nous introduisons une nouvelle représentation pour les BTFs qui isole les effets de parallaxes des autres effets. D'une part, nous construisons une BTF aplatie ("flattened") guidée par une paramétrisation spatiale et globale de la méso-géométrie sous-jacente. D'autre part, nous générons un ensemble de table d'indirections dans cette paramétrisation et pour chaque point de vue, afin d(encoder tous les effets de parallaxe. Nous analysons aussi cette représentation sur un ensemble de BTFs synthétiques afin de montrer l'avantage qu'elle apporte pour la cohérence dépendante du point de vue et pour trouver la meilleure stratégie d'échantillonnage. Nous montrons aussi que cette représentation est particulièrement bien adaptée pour bénéficier de l'accélération matérielle des processeurs graphiques actuels

Statistical Approaches to Inferring Object Shape from Single Images

Depth inference is a fundamental problem of computer vision with a broad range of potential applications. Monocular depth inference techniques, particularly shape from shading dates back to as early as the 40's when it was first used to study the shape of the lunar surface. Since then there has been ample research to develop depth inference algorithms using monocular cues. Most of these are based on physical models of image formation and rely on a number of simplifying assumptions that do not hold for real world and natural imagery. Very few make use of the rich statistical information contained in real world images and their 3D information. There have been a few notable exceptions though. The study of statistics of natural scenes has been concentrated on outdoor scenes which are cluttered. Statistics of scenes of single objects has been less studied, but is an essential part of daily human interaction with the environment. Inferring shape of single objects is a very important computer vision problem which has captured the interest of many researchers over the past few decades and has applications in object recognition, robotic grasping, fault detection and Content Based Image Retrieval (CBIR). This thesis focuses on studying the statistical properties of single objects and their range images which can benefit shape inference techniques. I acquired two databases: Single Object Range and HDR (SORH) and the Eton Myers Database of single objects, including laser-acquired depth, binocular stereo, photometric stereo and High Dynamic Range (HDR) photography. I took a data driven approach and studied the statistics of color and range images of real scenes of single objects along with whole 3D objects and uncovered some interesting trends in the data. The fractal structure of natural images was previously well known, and thought to be a universal property. However, my research showed that the fractal structure of single objects and surfaces is governed by a wholly different set of rules. Classical computer vision problems of binocular and multi-view stereo, photometric stereo, shape from shading, structure from motion, and others, all rely on accurate and complete models of which 3D shapes and textures are plausible in nature, to avoid producing unlikely outputs. Bayesian approaches are common for these problems, and hopefully the findings on the statistics of the shape of single objects from this work and others will both inform new and more accurate Bayesian priors on shape, and also enable more efficient probabilistic inference procedures

Evaluation of excavated surface irregularities and hardness of mechanical excavations and their relationship with excavator performance

This research involved lab and numerical excavation of a clastic sedimentary rock (Roubidoux Sandstone) using a long-bladed disc cutter in a Linear Rock Cutting Machine (LCM) with the aim of establishing relationships between the cutting parameters, excavated surface parameters (underbreaks, overbreaks and hardness), and performance parameters (specific energy and cutting rate). Three-dimensional cutting forces were recorded during the linear cutting. A structured laser imaging system was used to image the excavated surfaces for the estimation of the irregularities (ridge volumes (RV) and overbreak volumes (OV)). The excavated surface hardness was measured using the N-type Schmidt hammer. The numerical simulation was conducted in Itasca’s Particle Flow Code 3D (PFC3D). It involved model calibration, a study of the effects of the cutting geometry and cutter scale on the cutting forces, validation of the models using the lab cutting data, and a study of the effects of cutter size on the cutting forces. The results showed that the RV increased with increasing spacing-penetration (s-p) ratio for s-p ratios at which relieved cutting was achieved. However, the RV decreased with increasing s-p ratio under unrelieved cutting. The OV had a negative linear correlation with the s-p ratio under relieved cutting. In unrelieved cutting, the OV was independent of the s-p ratios. These findings can be used to determine the s-p ratio at which relieved cutting is first achieved. The specific energy decreased linearly with increasing surface hardness. The hardness was used together with the s-p ratio to develop a function for estimating SE. The numerical models yielded logarithmic functions for scaling forces from linear rock cutting simulations in PFC3D --Abstract, page iii

The review of methods for documentation, management and sustainability of cultural heritage. Case study: Museum of King Jan III’s Palace at Wilanów

All countries around the world are blessed with particularly rich cultural heritage. Nowadays, many researchers are exploring different methods for documentation, management and sustainability of cultural heritage. The aim of this article is to review the state of the art documentation, management and sustainability techniques in the field of cultural heritage based on the case study in the Museum of King Jan III’s Palace at Wilanów. Various 2D/3D image- and range-based methods are discussed demonstrating their applications and drawbacks. The geographical information system (GIS) is presented as a method for management, storage and maintenance of cultural heritage documentation

Photometric Reconstruction from Images: New Scenarios and Approaches for Uncontrolled Input Data

The changes in surface shading caused by varying illumination constitute an important cue to discern fine details and recognize the shape of textureless objects. Humans perform this task subconsciously, but it is challenging for a computer because several variables are unknown and intermix in the light distribution that actually reaches the eye or camera. In this work, we study algorithms and techniques to automatically recover the surface orientation and reflectance properties from multiple images of a scene. Photometric reconstruction techniques have been investigated for decades but are still restricted to industrial applications and research laboratories. Making these techniques work on more general, uncontrolled input without specialized capture setups has to be the next step but is not yet solved. We explore the current limits of photometric shape recovery in terms of input data and propose ways to overcome some of its restrictions. Many approaches, especially for non-Lambertian surfaces, rely on the illumination and the radiometric response function of the camera to be known. The accuracy such algorithms are able to achieve depends a lot on the quality of an a priori calibration of these parameters. We propose two techniques to estimate the position of a point light source, experimentally compare their performance with the commonly employed method, and draw conclusions which one to use in practice. We also discuss how well an absolute radiometric calibration can be performed on uncontrolled consumer images and show the application of a simple radiometric model to re-create night-time impressions from color images. A focus of this thesis is on Internet images which are an increasingly important source of data for computer vision and graphics applications. Concerning reconstructions in this setting we present novel approaches that are able to recover surface orientation from Internet webcam images. We explore two different strategies to overcome the challenges posed by this kind of input data. One technique exploits orientation consistency and matches appearance profiles on the target with a partial reconstruction of the scene. This avoids an explicit light calibration and works for any reflectance that is observed on the partial reference geometry. The other technique employs an outdoor lighting model and reflectance properties represented as parametric basis materials. It yields a richer scene representation consisting of shape and reflectance. This is very useful for the simulation of new impressions or editing operations, e.g. relighting. The proposed approach is the first that achieves such a reconstruction on webcam data. Both presentations are accompanied by evaluations on synthetic and real-world data showing qualitative and quantitative results. We also present a reconstruction approach for more controlled data in terms of the target scene. It relies on a reference object to relax a constraint common to many photometric stereo approaches: the fixed camera assumption. The proposed technique allows the camera and light source to vary freely in each image. It again avoids a light calibration step and can be applied to non-Lambertian surfaces. In summary, this thesis contributes to the calibration and to the reconstruction aspects of photometric techniques. We overcome challenges in both controlled and uncontrolled settings, with a focus on the latter. All proposed approaches are shown to operate also on non-Lambertian objects

On 3-D Surface Reconstruction Using Shape from Shadows

In this paper we discuss new results on the Shape From Darkness problem: using the motion of cast shadows to recover scene structure. Our approach is based on collecting a set of images from a fixed viewpoint as a known light source moves "across the sky". Previously published solutions to this problem have performed the reconstruction only for cross sections of the scene. In this paper, we present a reconstruction algorithm and discuss the reconstruction of an entire 3-D scene under various light source trajectories. We also consider the constraints on reconstruction. We conclude with experimental results that illustrate the convergence properties of the solution process and its robustness properties. I. Introduction In this paper, we consider surface reconstruction from shadow information. That is, to use the shape and geometric properties of observed shadows to infer the shape of the surfaces casting the shadows as well as those that the shadows are cast upon. This problem is somet..