Beschreibung
This book is a collection representing some of the most powerful and useful computer techniques in the service of art. Combining contributions from peer-reviewed journals of computer vision, image analysis, and art history with others written expressly for this volume, it presents a wide range of advanced computer imaging methods applied to the study of art. The book clarifies the assumptions underlying the possible use of each algorithm, provides examples of use and some of the art historical lessons learned through this use, and highlights available software. Art conservators, art historians, art educators, history students, computer image analysts, and computer graphics specialists will desire this fascinating volume. Zusatztext
Autorenportrait
Dr. David G. Stork is a graduate of MIT and the University of Maryland and studied art history at Wellesley College. He is an Adjunct Professor at Stanford University. Dr. Stork holds 64 U.S. patents and has published over 220 peer-reviewed scholarly works in machine learning, pattern recognition, computational optics, and image understanding of art. His many books include Seeing the Light, Pattern Classification Second Edition, and HAL's Legacy. He is a Fellow of IEEE, OSA, SPIE, IS&T, IAPR, IARIA, and AAIA, and a 2023 Leonardo@Djerassi Fellow.
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