Machine Learning in Computer Vision / Computational Imaging and Vision Bd.29 (PDF)
(Sprache: Englisch)
It started withimageprocessing inthesixties. Back then, it took ages to digitize a Landsat image and then process it with a mainframe computer. P- cessing was inspired on theachievements of signal processing and was still very much oriented towards...
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It started withimageprocessing inthesixties. Back then, it took ages to digitize a Landsat image and then process it with a mainframe computer. P- cessing was inspired on theachievements of signal processing and was still very much oriented towards programming. In the seventies, image analysis spun off combining image measurement with statistical pattern recognition. Slowly, computational methods detached themselves from the sensor and the goal to become more generally applicable. In theeighties, model-drivencomputervision originated when arti?cial- telligence and geometric modelling came together with image analysis com- nents. The emphasis was on precise analysiswithlittleorno interaction, still very much an art evaluated by visual appeal. The main bottleneck was in the amount of data using an average of 5 to 50 pictures to illustrate the point. At the beginning of the nineties, vision became available to many with the advent of suf?ciently fast PCs. The Internet revealed the interest of the g- eral public im images, eventually introducingcontent-basedimageretrieval. Combining independent (informal) archives, as the web is, urges for inter- tive evaluation of approximate results andhence weak algorithms and their combination in weak classi?ers.
Bibliographische Angaben
- Autoren: Nicu Sebe , Ira Cohen , Ashutosh Garg , Thomas S. Huang
- 2005, 2005, 242 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 1402032757
- ISBN-13: 9781402032752
- Erscheinungsdatum: 04.10.2005
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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Pressezitat
"This book comes right on time [...] It is amazing so early in a new field that a book appears which connects theory to algorithms and through them to convincing applications. [...] This book will surely be with us for quite some time to come."From the foreword by Arnold Smeulders
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