The purpose of this study is to determine whether viewing photos of muscular men or viewing photos of toned men produces greater body dissatisfaction scores for male college students. Prior to receiving the intervention, participants completed a pretest measuring their body satisfaction. The intervention was administered in a group setting and took approximately 30 minutes to administer. After receiving the intervention, participants completed the same assessment measures as the pre-test, but in a post-test form. Results indicate that there was a significant difference between pre-test and posttest body satisfaction ratings for men who viewed muscle photos and mend who viewed toned photos. This study contributes to a growing area of body image and Body Dysmorphic Disorder research in men. It also provides evidence for the benefits of addressing body satisfaction during the treatment of Body Dysmorphic Disorder.

The purpose of this thesis is to develop various advanced linear algebra techniques that apply to image processing. With the increasing use of computers and digital photography, being able to manipulate digital images efficiently and with greater freedom is extremely important. By applying the tools of linear algebra, we hope to improve the ability to process such images. We are especially interested in developing techniques that allow computers to manipulate images with the least amount of human guidance. In Chapter 2 and Chapter 3, we develop the basic definitions and linear algebra concepts that lay the foundation for later chapters. Then, in Chapter 4, we demonstrate techniques that allow a computer to rotate an image to the correct orientation automatically, and similarly, for the computer to correct a certain class of color distortion automatically. In both cases, we use certain properties of the eigenvalues and eigenvectors of covariance matrices. We then model color clashing and color variation in Chapter 5 using a powerful tool from linear algebra known as the Perron-Frobenius theorem. Finally, we explore ways to determine whether an image is a blur of another image using invariant functions. The inspiration behind these functions are recent applications of Lie Groups and Lie algebra to image processing.

No description available.

Abstract not available

This thesis involves the development of a three-dimensional measurement system for digitising the surface of an object. The measurement system consists of a single camera and a four point planar target of known size. The target is hand held, and is used to probe the surface of the object being measured. The position of the target is tracked by the camera, and the contact point on the object is determined. The vision based digitising technique can be used in the industrial and engineering design fields during the product development phase. The accuracy of measurement is an important criterion for establishing the success of the 3-D measurement system, and the factors influencing the accuracy are investigated. These factors include the image processing algorithm, the intrinsic parameters of the camera, the algorithm to determine the position, and various procedural variables. A new iterative algorithm is developed to calculate position. This algorithm is evaluated, and its performance is compared to that of an analytic algorithm. Simple calibration procedures are developed to determine the intrinsic parameters, and mathematical models are constructed to justify these procedures. The performance of the 3-D measurement system is established and compared to that of existing digitising systems.

This thesis is concerned with fundamental algorithms for estimating parameters of geometric models that are particularly relevant to computer vision. A general framework is considered which accommodates several important problems involving estimation in a maximum likelihood setting. By considering a special form of a commonly used cost function, a new, iterative, estimation method is evolved. This method is subsequently expanded to enable incorporation of a so-called ancillary constraint. An important feature of these methods is that they can serve as a basis for conducting theoretical comparison of various estimation approaches. Two specific applications are considered: conic fitting, and estimation of the fundamental matrix (a matrix arising in stereo vision). In the case of conic fitting, unconstrained methods are first treated. The problem of producing ellipse-specific estimates is subsequently tackled. For the problem of estimating the fundamental matrix, the new constrained method is applied to generate an estimate which satisfies the necessary rank-two constraint. Other constrained and unconstrained methods are compared within this context. For both of these example problems, the unconstrained and constrained methods are shown to perform with high accuracy and efficiency. The value of incorporating covariance information characterising the uncertainty of measured image point locations within the estimation process is also explored. Covariance matrices associated with data points are modelled, then an empirical study is made of the conditions under which covariance information enables generation of improved parameter estimates. Under the assumption that covariance information is, in itself, subject to estimation error, tests are undertaken to determine the effect of imprecise information upon the quality of parameter estimates. Finally, these results are carried over to experiments to assess the value of covariance information in estimating the fundamental matrix from real images. The use of such information is shown to be of potential benefit when the measurement process of image features is considered. / Thesis (Ph.D.)--School of Computer Science, 2004.

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

<p>This thesis presents and examines a method that can potentially be used for extracting parameters from a manifold in a space. In the thesis the method is presented, and a potential application is described. The application is determining FAP-values. FAP-values</p><p>are used for parameterizing faces, which can e.g. be used to compress data when sending video sequences over limited bandwidth.</p>

<p>When studying how companies differentiate from their competitors, corporate image can play a main role in this aspect. The aim of this study is to observe and analyse the perception by the consumers of the corporate image of two groceries companies.This perception can lead to a competitive position in the marketplace by outperforming competitors in all the areas of corporate image. Thus, it can be observed how both companies are differentiated in the mind of the consumers in a different way.</p>

<p>The cylinder liners surface is of major importance in an engine since it interacts with the piston rings and creates a tribologic system. This tribologic system has to be qualified and controlled in order to understand and control wear, oil consumption and shelf life. In this purpose, a program has been created in order to analyze SEM pictures and from them qualify the surface.</p><p>The aim of the project presented here has been to improve the preliminary steps leading to the image computation by standardizing the picture acquisition and improve the image filtering.</p>