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For about 20 years, evolutionary computation (as it provides a useful set of tools to deal with hard real-world problems) has been exploited in image processing and computer vision. This has lead to the establishment of an emergent research topic named evolutionary computer vision (ECV). Olague’s book aims to lay the foundations of this interdisciplinary research topic, concentrating particularly on goal-driven vision. To my mind, Dr. Gustavo Olague is certainly among the first and most active researchers of the evolutionary computer vision domain. He is Professor of Computer Science at CICESE in Tijuana, Mexico, where he founded the EvoVision group research group, which is dedicated to ECV. His background is in computer vision. He obtained his Ph.D. at the French National Polytechnic Institute of Grenoble associated with an INRIA research team, renowned for his high quality research in robotic vision. Unlike most ECV researchers, who are experts in stochastic optimisation and who address image processing and robot vision problems as challenging applications of their favourite evolutionary optimisation algorithms, Gustavo Olague is among the very few people able to have a foot in both optimisation and in computer vision. The development of artificial vision systems has been based on various analogies with biology and nature-inspired paradigms (stereovision or pattern recognition, for instance). Natural evolution is another source of inspiration and the main topic this book. But with an additional pinch of salt: natural vision systems are the result of millennia of evolution. So we may expect they are optimal in some sense, still to be unravelled. In this book, through questioning in a theoretical, philosophical, and

Gustavo Olague: Evolutionary computer vision, the first footprints