Craig Robertson

Finding Surface Correspondance for Object Recognition and Registration Using Pairwise Geometric Histograms

Pairwise geometric histograms have been demonstrated as an effective descriptor of arbitrary 2-dimensional shape which enable robust and efficient object recognition in complex scenes. In this paper we describe how the approach can be extended to allow the representation and classification of arbitrary 2 1/2- and 3-dimensional surface shape. This novel representation can be used in important vision tasks such as the recognition of objects with complex free-form surfaces and the registration of surfaces for building 3-dimensional models from multiple views. We apply this new representation to both of these tasks and present some promising results.

Object reconstruction by incorporating geometric constraints in reverse engineering

This paper deals with the constrained reconstruction of 3D geometric models of objects from range data. It describes a new technique of global shape improvement based upon feature positions and geometric constraints. It suggests a general incremental framework whereby constraints can be added and integrated in the model reconstruction process, resulting in an optimal trade-off between minimization of the shape fitting error and the constraint tolerances. After defining sets of constraints for planar and special case quadric surface classes based on feature coincidence, position and shape, the paper shows through application on synthetic model that our scheme is well behaved. The approach is then validated through experiments on different real parts. This work is the first to give such a large framework for the integration of geometric relationships in object modelling. The technique is expected to have a great impact in reverse engineering applications and manufactured object modelling where the majority of parts are designed with intended feature relationships.

Parallel evolutionary registration of range data

Most range data registration techniques are variants on the iterative closest point (ICP) algorithm, proposed by Y. Chen and G. Medioni (1991, Proceedings of the IEEE Conference on Robotics and Automation) and P. J. Besl and N. D. McKay ( 1992, IEEE Trans. Pattern Anal. Mach. Intell. 14, 239-256). That algorithm, though, is only one approach to optimizing a least-squares point correspondence sum proposed by K. S. Arun. T. Huang, and S. D. Blostein (1987, IEEE Trans. Pattern Anal. Mach. Intell, 9, 698-700). In its basic form ICP has many problems, for example, its reliance on preregistration by hand close to the global minimum and its tendency to converge to suboptimal or incorrect solutions. This paper reports on an evolutionary registration algorithm which does not require initial prealignment and has a very broad basin of convergence. It searches many areas of a registration parameter space in parallel and has available to it a selection of evolutionary techniques to avoid local minima which plague both ICP and its variants.

Dictionary of Computer Vision and Image Processing

Written by leading researchers, the 2nd Edition of the Dictionary of Computer Vision & Image Processing is a comprehensive and reliable resource which now provides explanations of over 3500 of the most commonly used terms across image processing, computer vision and related fields including machine vision. It offers clear and concise definitions with short examples or mathematical precision where necessary for clarity that ultimately makes it a very usable reference for new entrants to these fields at senior undergraduate and graduate level, through to early career researchers to help build up knowledge of key concepts. As the book is a useful source for recent terminology and concepts, experienced professionals will also find it a valuable resource for keeping up to date with the latest advances. New features of the 2nd Edition:Contains more than 1000 new terms, notably an increased focus on image processing and machine vision terms;Includes the addition of reference links across the majority of terms pointing readers to further information about the concept under discussion so that they can continue to expand their understanding;Now available as an eBook with enhanced content: approximately 50 videos to further illustrate specific terms; active cross-linking between terms so that readers can easily navigate from one related term to another and build up a full picture of the topic in question; and hyperlinked references to fully embed the text in the current literature.

A low-cost range finder using a visually located, structured light source

In this paper we show how the cost of a structured light, range finding system can be substantially reduced by visually tracking the structured light source. To be able to recover range measurements using a structured light range finder the relative positions of the structured light source and light sensor must be known. This is typically achieved by carefully controlling the position of at least one of these components using expensive mechanical actuators. Instead, we propose that little or no control is placed on the positioning of these components and that the position of the structured light source is determined using visual feedback. A low-cost prototype system employing this principle is presented.

Modelling Objects having Quadric Surfaces Incorporating Geometric cCnstraints

This paper deals with the constrained shape reconstruction of objects having quadric patches. The incorporation of geometric constraints in object reconstruction was used first by Porrill [10]. His approach combined the Kalman filter equations with linearized constraint equations. This technique was improved by De Geeter et al [5] to reduce the effects of linearization error. The nature and the specificity of this technique make it limited in scope and application.

Fitting of Constrained Feature Models to Poor 3D Data

In this work we have addressed the question of whether it is possible to extract parametric models of features from poor quality 3D data. In doing so we have examined the applicability of an evolutionary strategy to the problem of fitting constrained parametric models. In the first phase,-a background surface is fitted and removed leaving points of discontinuity associated with the feature. Then the discontinuities are classified, using the RANSAC algorithm, into drilled hole artifacts or blade edges suggesting drilled slots. This information, as well as the set of discontinuity points is passed to the Genocop III algorithm, proposed by Michalewicz [3], for optimization using a priori geometric constraints. Results, example times for convergence and comparisons with known ground truths are given.

Faithful recovering of quadric surfaces from 3D range data

The paper proposes a reliable method for estimating quadric surfaces from 3D range data in the framework of object recognition and localization or object modelling. Instead of estimating a quadric surface individually, the approach fits all the surfaces captured in the scene together, taking into account the geometric relationships between them and their specific characteristics. The technique is compared with other methods through experiments performed on real objects.

Aligning Arbitrary Surfaces using Pairwise Geometric Histograms

In this paper we present a novel representation for arbitrary surfaces that enables local correspondences to be determined. We then describe how these local correspondences can be used to search for the transformation that best aligns all of surface data. If this transformation is found to align a significant proportion of the surface data then the surfaces are said to have a correspondence.

Investigating Evolutionary Optimisation of Constrained Functions to Capture Shape Descriptions from Range Data

This paper examines the application of an evolutionary algorithm (GENO-COP III) to the problem of fitting surfaces and lines to both 2D synthetic and real 3D range data. The fitting is performed with both non-linear (domain) constraints and with non-linear (geometric and relational) constraints. Example fittings are given as well as an explanation of experimantal caveats that should be addressed when using this kind of approach. We have discovered, for example, that the time to generate starting reference points on the solution manifold is a significant part of the experiment time.