Hierarchically grouped 2D local features applied to edge contour localisation

One of the most significant research topics in computer vision is object detection. Most of the reported object detection results localise the detected object within a bounding box, but do not explicitly label the edge contours of the object. Since object contours provide a fundamental diagnostic of object shape, some researchers have initiated work on linear contour feature representations for object detection and localisation. However, linear contour feature-based localisation is highly dependent on the performance of linear contour detection within natural images, and this can be perturbed significantly by a cluttered background. In addition, the conventional approach to achieving rotation-invariant features is to rotate the feature receptive field to align with the local dominant orientation before computing the feature representation. Grid resampling after rotation adds extra computational cost and increases the total time consumption for computing the feature descriptor. Though it is not an expensive process if using current computers, it is appreciated that if each step of the implementation is faster to compute especially when the number of local features is increasing and the application is implemented on resource limited ”smart devices”, such as mobile phones, in real-time. Motivated by the above issues, a 2D object localisation system is proposed in this thesis that matches features of edge contour points, which is an alternative method that takes advantage of the shape information for object localisation. This is inspired by edge contour points comprising the basic components of shape contours. In addition, edge point detection is usually simpler to achieve than linear edge contour detection. Therefore, the proposed localization system could avoid the need for linear contour detection and reduce the pathological disruption from the image background. Moreover, since natural images usually comprise many more edge contour points than interest points (i.e. corner points), we also propose new methods to generate rotation-invariant local feature descriptors without pre-rotating the feature receptive field to improve the computational efficiency of the whole system. In detail, the 2D object localisation system is achieved by matching edge contour points features in a constrained search area based on the initial pose-estimate produced by a prior object detection process. The local feature descriptor obtains rotation invariance by making use of rotational symmetry of the hexagonal structure. Therefore, a set of local feature descriptors is proposed based on the hierarchically hexagonal grouping structure. Ultimately, the 2D object localisation system achieves a very promising performance based on matching the proposed features of edge contour points with the mean correct labelling rate of the edge contour points 0.8654 and the mean false labelling rate 0.0314 applied on the data from Amsterdam Library of Object Images (ALOI). Furthermore, the proposed descriptors are evaluated by comparing to the state-of-the-art descriptors and achieve competitive performances in terms of pose estimate with around half-pixel pose error.

Transforming transformation optics via generalised refraction

Generalised refraction is a topic which has, thus far, garnered far less attention than it deserves. The purpose of this thesis is to highlight the potential that generalised refraction has to offer with regards to imaging and its application to designing new passive optical devices. Specifically in this thesis we will explore two types of gener- alised refraction which takes place across a planar interface: refraction by generalised confocal lenslet arrays (gCLAs), and refraction by ray-rotation sheets. We will show that the corresponding laws of refraction for these interfaces produce, in general, light-ray fields with non-zero curl, and as such do not have a corresponding outgoing waveform. We will then show that gCLAs perform integral, geometrical imaging, and that this enables them to be considered as approximate realisations of metric tensor interfaces. The concept of piecewise transformation optics will be introduced and we will show that it is possible to use gCLAs along with other optical elements such as lenses to design simple piecewise transformation-optics devices such as invisibility cloaks and insulation windows. Finally, we shall show that ray-rotation sheets can be interpreted as performing geometrical imaging into complex space, and that as a consequence, ray-rotation sheets and gCLAs may in fact be more closely related than first realised. We conclude with a summary of potential future projects which lead naturally from the results of this thesis.