Ebook: Performance Characterization in Computer Vision

This edited volume addresses a subject which has been discussed inten­ sively in the computer vision community for several years. Performance characterization and evaluation of computer vision algorithms are of key importance, particularly with respect to the configuration of reliable and ro­ bust computer vision systems as well as the dissemination of reconfigurable systems in novel application domains. Although a plethora of literature on this subject is available for certain' areas of computer vision, the re­ search community still faces a lack of a well-grounded, generally accepted, and--eventually-standardized methods. The range of fundamental problems encoIl!passes the value of synthetic images in experimental computer vision, the selection of a representative set of real images related to specific domains and tasks, the definition of ground truth given different tasks and applications, the design of experimental test­ beds, the analysis of algorithms with respect to general characteristics such as complexity, resource consumption, convergence, stability, or range of admissible input data, the definition and analysis of performance measures for classes of algorithms, the role of statistics-based performance measures, the generation of data sheets with performance measures of algorithms sup­ porting the system engineer in his configuration problem, and the validity of model assumptions for specific applications of computer vision.

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This book addresses a subject which has been discussed intensively in the computer vision community for several years. Performance characterization and evaluation of computer vision algorithms are of key importance, particularly with respect to the configuration of reliable and robust computer vision systems as well as the dissemination of reconfigurable systems in novel application domains.
The objective of this volume is to provide a scientific foundation for performance characterization of computer vision methods, to give an overview of methodologies of comparative assessment of algorithms and to present evaluation approaches for a variety of computer vision applications.
This volume comprises six parts: general issues; methodological aspects; statistical aspects; comparative studies; selected methods and algorithms; and finally a domain-specific part on evaluation in medical imaging.
Audience: This book can be read by both specialists and graduate students in computer science and electrical engineering who take an interest in computer vision, image processing, and algorithms.

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This book addresses a subject which has been discussed intensively in the computer vision community for several years. Performance characterization and evaluation of computer vision algorithms are of key importance, particularly with respect to the configuration of reliable and robust computer vision systems as well as the dissemination of reconfigurable systems in novel application domains.
The objective of this volume is to provide a scientific foundation for performance characterization of computer vision methods, to give an overview of methodologies of comparative assessment of algorithms and to present evaluation approaches for a variety of computer vision applications.
This volume comprises six parts: general issues; methodological aspects; statistical aspects; comparative studies; selected methods and algorithms; and finally a domain-specific part on evaluation in medical imaging.
Audience: This book can be read by both specialists and graduate students in computer science and electrical engineering who take an interest in computer vision, image processing, and algorithms.
Content:
Front Matter....Pages i-xvi
Front Matter....Pages 1-1
Experiences with Empirical Evaluation of Computer Vision Algorithms....Pages 3-16
Evaluation and Validation of Computer Vision Algorithms....Pages 17-28
Databases for Performance Characterization....Pages 29-40
Quality in Computer Vision....Pages 41-51
Front Matter....Pages 53-53
The Role of Theory in the Evaluation of Image Motion Algorithms....Pages 55-67
Motion Extraction....Pages 69-80
Principles of Constructing a Performance Evaluation Protocol for Graphics Recognition Algorithms....Pages 81-90
Dissimilarity Measures between Gray-Scale Images as a Tool for Performance Assessment....Pages 91-92
Front Matter....Pages 93-93
Propagating Covariance in Computer Vision....Pages 95-114
Input Guided Performance Evaluation....Pages 115-124
Uncertainty Propagation in Shape Reconstruction and Moving Object Detection from Optical Flow....Pages 125-135
Front Matter....Pages 137-137
Performance Characteristics of Low-Level Motion Estimators in Spatiotemporal Images....Pages 139-152
Evaluation of Numerical Solution Schemes for Differential Equations....Pages 153-166
Experimental Comparative Evaluation of Feature Point Tracking Algorithms....Pages 167-178
Front Matter....Pages 179-179
Evaluation of an Optical Flow Method for Measuring 2D and 3D Corn Seedling Growth....Pages 181-194
Unsupervised Learning for Robust Texture Segmentation....Pages 195-209
Confidence of Ground Control for Validating Stereo Terrain Reconstruction....Pages 211-225
Performance Analysis of Shape Recovery by Random Sampling and Voting....Pages 227-240
Multigrid Convergence Based Evaluation of Surface Approximations....Pages 241-253
Sensitivity Analysis of Projective Geometry 3D Reconstruction....Pages 255-264
Front Matter....Pages 179-179
A Systematic Approach to Error Sources for the Evaluation and Validation of a Binocular Vision System for Robot Control....Pages 265-272
Front Matter....Pages 273-273
Error Metrics for Quantitative Evaluation of Medical Image Segmentation....Pages 275-284
Performance Characterization of Landmark Operators....Pages 285-297
Model-Based Evaluation of Image Segmentation Methods....Pages 299-311
Back Matter....Pages 313-317

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This book addresses a subject which has been discussed intensively in the computer vision community for several years. Performance characterization and evaluation of computer vision algorithms are of key importance, particularly with respect to the configuration of reliable and robust computer vision systems as well as the dissemination of reconfigurable systems in novel application domains.
The objective of this volume is to provide a scientific foundation for performance characterization of computer vision methods, to give an overview of methodologies of comparative assessment of algorithms and to present evaluation approaches for a variety of computer vision applications.
This volume comprises six parts: general issues; methodological aspects; statistical aspects; comparative studies; selected methods and algorithms; and finally a domain-specific part on evaluation in medical imaging.
Audience: This book can be read by both specialists and graduate students in computer science and electrical engineering who take an interest in computer vision, image processing, and algorithms.
Content:
Front Matter....Pages i-xvi
Front Matter....Pages 1-1
Experiences with Empirical Evaluation of Computer Vision Algorithms....Pages 3-16
Evaluation and Validation of Computer Vision Algorithms....Pages 17-28
Databases for Performance Characterization....Pages 29-40
Quality in Computer Vision....Pages 41-51
Front Matter....Pages 53-53
The Role of Theory in the Evaluation of Image Motion Algorithms....Pages 55-67
Motion Extraction....Pages 69-80
Principles of Constructing a Performance Evaluation Protocol for Graphics Recognition Algorithms....Pages 81-90
Dissimilarity Measures between Gray-Scale Images as a Tool for Performance Assessment....Pages 91-92
Front Matter....Pages 93-93
Propagating Covariance in Computer Vision....Pages 95-114
Input Guided Performance Evaluation....Pages 115-124
Uncertainty Propagation in Shape Reconstruction and Moving Object Detection from Optical Flow....Pages 125-135
Front Matter....Pages 137-137
Performance Characteristics of Low-Level Motion Estimators in Spatiotemporal Images....Pages 139-152
Evaluation of Numerical Solution Schemes for Differential Equations....Pages 153-166
Experimental Comparative Evaluation of Feature Point Tracking Algorithms....Pages 167-178
Front Matter....Pages 179-179
Evaluation of an Optical Flow Method for Measuring 2D and 3D Corn Seedling Growth....Pages 181-194
Unsupervised Learning for Robust Texture Segmentation....Pages 195-209
Confidence of Ground Control for Validating Stereo Terrain Reconstruction....Pages 211-225
Performance Analysis of Shape Recovery by Random Sampling and Voting....Pages 227-240
Multigrid Convergence Based Evaluation of Surface Approximations....Pages 241-253
Sensitivity Analysis of Projective Geometry 3D Reconstruction....Pages 255-264
Front Matter....Pages 179-179
A Systematic Approach to Error Sources for the Evaluation and Validation of a Binocular Vision System for Robot Control....Pages 265-272
Front Matter....Pages 273-273
Error Metrics for Quantitative Evaluation of Medical Image Segmentation....Pages 275-284
Performance Characterization of Landmark Operators....Pages 285-297
Model-Based Evaluation of Image Segmentation Methods....Pages 299-311
Back Matter....Pages 313-317
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