Perceptual Qualities of Optically Mixed Materials

We present a novel setup in which real objects made of two different materials can be mixed optically in a linearly weighted manner. We conducted a psychophysical experiment in which observers rated optical mixtures of the three combinations of glossy, matte, and velvety green birds. The observers rated the materials on four scales: matte–glossy, hard–soft, cold–warm, and light-heavy. The judgments were found to be consistent and varied systematically with the weights of the contributions. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

An investigation into the efficacy of single low dose of insulin in the prevention of excessive cutaneous scarring in breast surgery

Early human fetuses have the ability to heal wounds by completely regenerating tissues, leaving no evidence of scarring. However in the adult scarring is the inevitable endpoint of the wound healing process. Sometimes these scars can be pathological in nature causing both functional and aesthetic problems to those affected. Every year millions of people around the globe acquire problematic or pathological scars either whilst undergoing surgery or from traumatic injuries and at present there remain a severely limited number of pharmacological treatment options to offer these patients. Importantly currently there exists no treatment that can either eliminate or reliably reduce acquired scars. Not only is the treatment of acquired scars problematic but also the clinical assessment of scars is largely subjective in nature and frequently relies on assessment scales that show large amounts of inter-rater variation and lack quantification. Especially subjective is the measurement of scar colour, which can be markedly different from the surrounding skin and cause significant distress to the patient. Without an objective assessment framework clinicians cannot reliably examine scars nor gauge responses to any treatment. The aim of this thesis is thus two-fold. Firstly a new anti-scarring treatment in the form of insulin will be tested in a randomised, double blind, intra-patient, placebo controlled trial where patients undergoing elective bilateral breast surgery will have low-dose insulin injected subcutaneously to one breast and placebo to the other at the time of surgery. Patients will be followed up for 12 months and their scars compared to examine the therapeutic effect of insulin upon scars. Secondly the thesis aims to test the validity of new methods of assessing the scar colour of a subset of patients within the insulin trial using previously untested photographic devices and software. These devices are hoped to add much needed quantification to scar assessment.Open Acces

The perception of material qualities in real-world images

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 135-146).One can easily tell if a sidewalk is slippery, if food is fresh, if a spoon is made of plastic or stainless steel, or if a suspicious looking mole warrants a trip to the doctor. This ability to visually identify and discriminate materials is known as material perception and little is known about it. We have measured human material judgments on a wide range of complex, real world materials. We have gathered several diverse image databases and made use of them to conduct psychophysical studies. We asked observers to classify surfaces and objects as being made of fabric, paper, plastic or other common material categories. In the first part of this thesis, we present experiments that establish that observers can make these judgments of material category reliably, quickly and in challenging conditions of rapid presentation. We find that categorization performance cannot be explained by simple, low-level cues like color or high spatial frequencies. In the second part of the thesis, we explore judgments beyond those of common material categories. Observers judged many dimensions of material appearance such as matte vs. glossy, opaque vs. translucent, rigid vs. nonrigid, soft vs. rough to touch, and even genuine vs. fake for familiar object categories like flowers, fruits and dessert. Observers were surprisingly accurate, even in 40 millisecond presentations. In the final part of this thesis, we compare the performance of state-of-art computer vision techniques with human performance on our images and tasks and find current techniques to be severely lacking.(cont.) Taken together, our findings indicate that material perception is a distinct mechanism and can be as fast and flexible as object recognition or scene perception. When recognizing materials, low-level image information is of limited use for both humans and computer vision systems. We conclude that material recognition is a rich and challenging problem domain and there is much ground to be covered in both visual perception and computer vision.by Lavanya Sharan.Ph.D

Assessment of plastics in the National Trust: a case study at Mr Straw's House

The National Trust is a charity that cares for over 300 publically accessible historic buildings and their contents across England, Wales and Northern Ireland. There have been few previous studies on preservation of plastics within National Trust collections, which form a significant part of the more modern collections of objects. This paper describes the design of an assessment system which was successfully trialled at Mr Straws House, a National Trust property in Worksop, UK. This system can now be used for future plastic surveys at other National Trust properties. In addition, the survey gave valuable information about the state of the collection, demonstrating that the plastics that are deteriorating are those that are known to be vulnerable, namely cellulose nitrate/acetate, PVC and rubber. Verifying this knowledge of the most vulnerable plastics enables us to recommend to properties across National Trust that these types should be seen as a priority for correct storage and in-depth recording

Advances in Planetary Geology

Advances in Planetary Geology is a new series intended to serve the planetary geology community with a form for quick and thorough communications. There are no set lists of acceptable topics or formats, and submitted manuscripts will not undergo a formal review. All submissions should be in a camera ready form, preferably spaced, and submitted to the editor

Surface reflectance recognition and real-world illumination statistics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2003.Includes bibliographical references (p. 141-150).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Humans distinguish materials such as metal, plastic, and paper effortlessly at a glance. Traditional computer vision systems cannot solve this problem at all. Recognizing surface reflectance properties from a single photograph is difficult because the observed image depends heavily on the amount of light incident from every direction. A mirrored sphere, for example, produces a different image in every environment. To make matters worse, two surfaces with different reflectance properties could produce identical images. The mirrored sphere simply reflects its surroundings, so in the right artificial setting, it could mimic the appearance of a matte ping-pong ball. Yet, humans possess an intuitive sense of what materials typically "look like" in the real world. This thesis develops computational algorithms with a similar ability to recognize reflectance properties from photographs under unknown, real-world illumination conditions. Real-world illumination is complex, with light typically incident on a surface from every direction. We find, however, that real-world illumination patterns are not arbitrary. They exhibit highly predictable spatial structure, which we describe largely in the wavelet domain. Although they differ in several respects from the typical photographs, illumination patterns share much of the regularity described in the natural image statistics literature. These properties of real-world illumination lead to predictable image statistics for a surface with given reflectance properties. We construct a system that classifies a surface according to its reflectance from a single photograph under unknown illumination. Our algorithm learns relationships between surface reflectance and certain statistics computed from the observed image.(cont.) Like the human visual system, we solve the otherwise underconstrained inverse problem of reflectance estimation by taking advantage of the statistical regularity of illumination. For surfaces with homogeneous reflectance properties and known geometry, our system rivals human performance.by Ron O. Dror.Ph.D

Surface Reflectance Recognition and Real-World Illumination Statistics

Humans distinguish materials such as metal, plastic, and paper effortlessly at a glance. Traditional computer vision systems cannot solve this problem at all. Recognizing surface reflectance properties from a single photograph is difficult because the observed image depends heavily on the amount of light incident from every direction. A mirrored sphere, for example, produces a different image in every environment. To make matters worse, two surfaces with different reflectance properties could produce identical images. The mirrored sphere simply reflects its surroundings, so in the right artificial setting, it could mimic the appearance of a matte ping-pong ball. Yet, humans possess an intuitive sense of what materials typically "look like" in the real world. This thesis develops computational algorithms with a similar ability to recognize reflectance properties from photographs under unknown, real-world illumination conditions. Real-world illumination is complex, with light typically incident on a surface from every direction. We find, however, that real-world illumination patterns are not arbitrary. They exhibit highly predictable spatial structure, which we describe largely in the wavelet domain. Although they differ in several respects from the typical photographs, illumination patterns share much of the regularity described in the natural image statistics literature. These properties of real-world illumination lead to predictable image statistics for a surface with given reflectance properties. We construct a system that classifies a surface according to its reflectance from a single photograph under unknown illuminination. Our algorithm learns relationships between surface reflectance and certain statistics computed from the observed image. Like the human visual system, we solve the otherwise underconstrained inverse problem of reflectance estimation by taking advantage of the statistical regularity of illumination. For surfaces with homogeneous reflectance properties and known geometry, our system rivals human performance

Image statistics and the perception of surface reflectance

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.MIT Institute Archives copy: p. 223 (last page) bound in reverse order.Includes bibliographical references (p. 217-223).Humans are surprisingly good at judging the reflectance of complex surfaces even when the surfaces are viewed in isolation, contrary to the Gelb effect. We argue that textural cues are important for this task. Traditional machine vision systems, on the other hand, are incapable of recognizing reflectance properties. Estimating the reflectance of a complex surface under unknown illumination from a single image is a hard problem. Recent work in reflectance recognition has shown that certain statistics measured o an image of a surface are diagnostic of reflectance. We consider opaque surfaces with medium scale structure and spatially homogeneous reflectance properties. For such surfaces, we find that statistics of intensity histograms and histograms of filtered outputs are indicative of the diffuse surface reflectance. We compare the performance of a learning algorithm that employs these image statistics to human performance in two psychophysical experiments. In the first experiment, observers classify images of complex surfaces according to the perceived reflectance. We find that the learning algorithm rivals human performance at the classification task. In the second experiment, we manipulate the statistics of images and ask observers to provide reflectance ratings. In this case, the learning algorithm performs similarly to human observers. These findings lead us to conclude that the image statistics capture perceptually relevant information.by Lavanya Sharan.S.M

Guideline on therapeutic dentistry for the 5-th term

РУКОВОДСТВАСТОМАТОЛОГИЯ ЛЕЧЕБНО-ВОССТАНОВИТЕЛЬНАЯСТОМАТОЛОГИЯ ТЕРАПЕВТИЧЕСКАЯИНОСТРАННЫЕ СТУДЕНТЫУЧЕБНО-МЕТОДИЧЕСКИЕ ПОСОБИЯПособие составлено в соответствии с учебной программой для медицинских вузов по терапевтической стоматологии. Предназначено для внутреннего использования

The determination of product lines for porcelain enamel jobbing shops

Thesis (M.B.A.)--Boston Universit