In this paper, we analyze the uniqueness of the sparse time frequency decomposition and investigate the efficiency of the nonlinear matching pursuit method. Under the assumption of scale separation, we show that the sparse time frequency decomposition is unique up to an error that is determined by the scale separation property of the signal. We further show that the unique decomposition can be ...

Schema matching is a critical step in many applications, such as data warehouse loading, Online Analytical Process (OLAP), Data mining, semantic web [2] and schema integration. This task is defined for finding the semantic correspondences between elements of two schemas. Recently, schema matching has found considerable interest in both research and practice. In this paper, we present a new impr...

The distance transform has been proposed for use in computer vision for a number of applications such as matching and skeletonisation. This paper proposes two things: (1) a multi-scale distance transform to overcome the need to choose edge thresholds and scale and (2) the addition of various saliency factors such as edge strength, length and curvature to the basic distance transform to improve ...

An automated method to register three-dimensional Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) brain images is presented. In a first step, mathematically well founded differential operators in scale space are applied to 2D or 3D CT and MRI images resulting in feature images depicting ’ridgeness’. In a second step, a fully automatic hierarchical correlation scheme is applied to ...

In real-time monitoring process, resolution must be set against field vision. There are two problems in the real-time monitoring procedures, which are: the field vision is too small to capture the target completely and a larger field vision with low resolution . In order to solve these problems, a new type of real-time panoramic monitoring systems becomes necessary. In this paper, we proposed a...

ii Acknowledgements I would like to thank my project supervisor, Dr Rob Irving, whose endless patience, advice and assistance has been greatly appreciated. I would also like to thank Dr Helen Purchase for her efforts in securing a faculty scholarship that has enabled me to attend the MSc Information Technology course over the last twelve months. Abstract The Scottish Foundation Allocation Schem...

Scale variation commonly arises in images/videos, which cannot be naturally dealt with by optical flow. Invariant feature matching, on the contrary, provides sparse matching and could fail for regions without conspicuous structures. We aim to establish dense correspondence between frames containing objects in different scales and contribute a new framework taking pixel-wise scales into consider...

This paper presents a framework for shape matching and classification through scalespace decomposition of 3D models. The algorithm is based on recent developments in efficient hierarchical decomposition of a point distribution in metric space ~p,d! using its spectral properties. Through spectral decomposition, we reduce the problem of matching to that of computing a mapping and distance measure...

The scale invariant feature transform (SIFT) is a widely used interest operator for supporting tasks such as 3D matching, 3D scene reconstruction, panorama stitching, image registration and motion tracking. Although SIFT is reported to be robust to disparate radiometric and geometric conditions in visible light imagery, using the default input parameters does not yield satisfactory results when...

APrIl 2017 IZA DP No. 10697 The Effects of Physical Restructuring on the Socioeconomic Status of Neighborhoods: Selective Migration and Upgrading In the last few decades, urban restructuring programs have been implemented in many Western European cities with the main goal of combating a variety of socioeconomic problems in deprived neighborhoods. The main instrument of restructuring has been ho...