Empirical evaluation techniques in computer vision

by Kevin Bowyer

Empirical Evaluation Techniques in Computer Vision presents methods that allow comparative assessment of algorithms and the accompanying benefits: places computer vision on solid experimental and scientific grounds, assists the development of engineering solutions to practical problems, allows accurate assessments of computer vision research, provides convincing evidence that computer vision research results in practical solutions. The chapters in this volume cover the three main paradigms for evaluating computer vision algorithms. The paradigms are: (1) evaluations that are independently administered, (2) evaluation of a set of algorithms by one research group, and (3) evaluation methods that feature ground truthing procedures as a major component.