Kim L. Boyer – författare

Perceptual Organization for Artificial Vision Systems is an edited collection of invited contributions based on papers presented at The Workshop on Perceptual Organization in Computer Vision, held in Corfu, Greece, in September 1999. The theme of the workshop was `Assessing the State of the Community and Charting New Research Directions.'Perceptual organization can be defined as the ability to impose structural regularity on sensory data, so as to group sensory primitives arising from a common underlying cause. This book explores new models, theories, and algorithms for perceptual organization.Perceptual Organization for Artificial Vision Systems includes contributions by the world's leading researchers in the field. It explores new models, theories, and algorithms for perceptual organization, as well as demonstrates the means for bringing research results and theoretical principles to fruition in the construction of computer vision systems. The focus of this collection is on the design of artificial vision systems. The chapters comprise contributions from researchers in both computer vision and human vision.

This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.

This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.

This book presents a comprehensive review of image processing methods, for the analysis of land use in residential areas. Combining a theoretical framework with highly practical applications, the book describes a system for the effective detection of single houses and streets in very high resolution. Topics and features: with a Foreword by Prof. Dr. Peter Reinartz of the German Aerospace Center; provides end-of-chapter summaries and review questions; presents a detailed review on remote sensing satellites; examines the multispectral information that can be obtained from satellite images, with a focus on vegetation and shadow-water indices; investigates methods for land-use classification, introducing precise graph theoretical measures over panchromatic images; addresses the problem of detecting residential regions; describes a house and street network-detection subsystem; concludes with a summary of the key ideas covered in the book.

Perceptual Organization for Artificial Vision Systems is an edited collection of invited contributions based on papers presented at The Workshop on Perceptual Organization in Computer Vision, held in Corfu, Greece, in September 1999. The theme of the workshop was `Assessing the State of the Community and Charting New Research Directions.'Perceptual organization can be defined as the ability to impose structural regularity on sensory data, so as to group sensory primitives arising from a common underlying cause. This book explores new models, theories, and algorithms for perceptual organization.Perceptual Organization for Artificial Vision Systems includes contributions by the world's leading researchers in the field. It explores new models, theories, and algorithms for perceptual organization, as well as demonstrates the means for bringing research results and theoretical principles to fruition in the construction of computer vision systems. The focus of this collection is on the design of artificial vision systems. The chapters comprise contributions from researchers in both computer vision and human vision.

Perceptual Organization for Artificial Vision Systems is an edited collection of invited contributions based on papers presented at The Workshop on Perceptual Organization in Computer Vision, held in Corfu, Greece, in September 1999. The theme of the workshop was `Assessing the State of the Community and Charting New Research Directions.'' Perceptual organization can be defined as the ability to impose structural regularity on sensory data, so as to group sensory primitives arising from a common underlying cause. This book explores new models, theories, and algorithms for perceptual organization. Perceptual Organization for Artificial Vision Systems includes contributions by the world''s leading researchers in the field. It explores new models, theories, and algorithms for perceptual organization, as well as demonstrates the means for bringing research results and theoretical principles to fruition in the construction of computer vision systems. The focus of this collection is on the design of artificial vision systems. The chapters comprise contributions from researchers in both computer vision and human vision.

This book constitutes the refereed proceedings of the 4th Mexican Conference on Pattern Recognition, MCPR 2012, held in Huatulco, Mexico, in June 2012. The 31 revised full papers and 3 keynotes presented were carefully reviewed and selected from 64 submissions and are organized in topical sections on image processing; computer vision and image recognition; pattern recognition and neural networks; and document processing and speech recognition.

This book constitutes the refereed proceedings of the 4th Mexican Conference on Pattern Recognition, MCPR 2012, held in Huatulco, Mexico, in June 2012. The 31 revised full papers and 3 keynotes presented were carefully reviewed and selected from 64 submissions and are organized in topical sections on image processing; computer vision and image recognition; pattern recognition and neural networks; and document processing and speech recognition.

This book addresses the range image registration problem for automatic 3D model construction. The focus is on obtaining highly precise alignments between different view pairs of the same object to avoid 3D model distortions; in contrast to most prior work, the view pairs may exhibit relatively little overlap and need not be prealigned. To this end, a novel effective evaluation metric for registration, the Surface Interpenetration Measure (SIM) is defined. This measure quantifies the interleaving of two surfaces as their alignment is refined, putting the qualitative evaluation of “splotchiness,” often used in reference to renderings of the aligned surfaces, onto a solid mathematical footing. The SIM is shown to be superior to mean squared error (i.e. more sensitive to fine scale changes) in controlling the final stages of the alignment process.The authors go on to combine the SIM with Genetic Algorithms (GAs) to develop a robust approach for range image registration. The results confirm that this technique achieves precise surface registration with no need for prealignment, as opposed to methods based on the Iterative Closest Point (ICP) algorithm, the most popular to date. Thorough experimental results including an extensive comparative study are presented and enhanced GA-based approaches to improve the registration still further are proposed. The authors also develop a global multiview registration technique using the GA-based approach. The results show considerable promise in terms of accuracy for 3D modeling.