2D and 3D Shape Descriptors

The field of computer vision studies the computational tools and methods required for computers to be able to process visual information, for example images and video. Shape descriptors are one of the tools commonly used in image processing applications. Shape descriptors are mathematical functions which are applied to an image and produce numerical values which are representative of a particular characteristic of the image. These numerical values can then be processed in order to provide some information about the image. For example, these values can be fed to a classifier in order to assign a class label to the image. There are a number of shape descriptors already existing in the literature for 2D and 3D images. The aim of this thesis is to develop additional shape descriptors which provide an improvement over (or an alternative to) those already existing in the literature. A large majority of the existing 2D shape descriptors use surface information to produce a measure. However, in some applications surface information is not present and only partially extracted contours are available. In such cases, boundary based shape descriptors must be used. A new boundary based shape descriptor called Linearity is introduced. This measure can be applied to open or closed curve segments. In general the availability of 3D images is comparatively smaller than that of 2D images. As a consequence, the number of existing 3D shape descriptors is also relatively smaller. However, there is an increasing interest in the development of 3D descriptors. In this thesis we present two basic 3D measures which afterwards are modified to produce a range of new shape descriptors. All of these descriptors are similar in their behaviour, however they can be combined and applied in different image processing applications such as image retrieval and classification. This simple fact is demonstrated through several examples.Mexican Science Council (Consejo Nacional de Ciencia y Tecnologia, CONACyT

A Tunable Measure of 3D Compactness

The field of shape description can be applied in domains ranging from medicine to engineering. Defining new metrics may allow to better describe shapes. It is therefore an essential process of development of the field. In this work, a new family of compactness metrics is introduced. It is proven that they range over (0, 1] and are translation, rotation and scaling independent. The sphere is the shape that has the smallest volume for a fixed surface, this is a definition of compactness. Therefore, the metrics of this family are called compactness measures since they all reach 1 if and only if the considered shape is a sphere. The different metrics of the family are obtained by the modification of a parameter β involved in the mathematical definition of the metric. They are proven to be different from each other and a thorough study of their behaviour resulted in the formulation of two interesting conjectures concerning the limit cases of β. Finally several experiments investigate how McGill’s database classes of shapes are represented when using the new family

Spatial and human factors affecting image quality and viewer experience of stereoscopic 3D in television and cinema

PhD ThesisThe horizontal offset in the two eyes’ locations in the skull means that they receive slightly different images of the world. The visual cortex uses these disparities to calculate where in depth different objects are, absolutely (physical distance from the viewer, perceived very imprecisely) and relatively (whether one object is in front of another, perceived with great precision). For well over a century, stereoscopic 3D (S3D) technology has existed which can generate an artificial sense of depth by displaying images with slight disparities to the different retinas. S3D technology is now considerably cheaper to access in the home, but remains a niche market, partly reflecting problems with viewer experience and enjoyment of S3D. This thesis considers some of the factors that could affect viewer experience of S3D content. While S3D technology can give a vivid depth percept, it can also lead to distortions in perceived size and shape, particularly if content is viewed at the wrong distance or angle. Almost all S3D content is designed for a viewing angle perpendicular to the screen, and with a recommended viewing distance, but little is known about the viewing distance typically used for S3D, or the effect of viewing angle. Accordingly, Chapter 2 of this thesis reports a survey of members of the British public. Chapters 3 and 4 report two experiments, one designed to assess the effect of oblique viewing, and another to consider the interaction between S3D and perceived size. S3D content is expensive to generate, hence producers sometimes “fake” 3D by shifting 2D content behind the screen plane. Chapter 5 investigates viewer experience with this fake 3D, and finds it is not a viable substitute for genuine S3D while also examining whether viewers fixate on different image features when video content is viewed in S3D, as compared to 2D.part-funded by BSkyB and EPSRC as a CASE PhD studentship supporting PH