Labeling Problems with Smoothness-Based Priors in Computer Vision: Formulations, Optimizations and Applications - Brossura

CHEN, Shifeng

Brossura

ISBN 10: 3843376425 ISBN 13: 9783843376426

Casa editrice: LAP LAMBERT Academic Publishing, 2010

Riassunto

Many applications in computer vision can be formulated as labeling problems of assigning each pixel a label where the labels represent some local quantities. To improve results of these labeling problems, smoothness-based priors can be enforced in the formulations.Such labeling problems with smoothness-based priors can be solved by minimizing a Markov energy. According to different definitions of the energy functions, different optimization tools can be used to obtain the results. In this book, three optimization approaches are used due to their good performance: graph cuts, belief propagation, and optimization with a closed form solution. Five algorithms in different applications are proposed in this book. All of them are formulated as smoothness based labeling problems, including single image segmentation, video object cutout, image/video completion, image denoising, and image matting. This book should be especially useful to professionals in computer vision fields.

Su questo libro

L'autore

Shifeng Chen, PhD: Studied Information Engineering at The Chinese University of Hong Kong, China. Research assistant professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, China.

Dettagli dell'edizione

• Editore: LAP LAMBERT Academic Publishing
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 3843376425
• ISBN 13: 9783843376426
• Rilegatura: Copertina flessibile
• Numero di pagine: 156
• Contatto del produttore: non disponibile
• Persona responsabile: KreGa Onlinehandel GmbH; 4950000000000; info@krega-onlinehandel.de; ; Birkenweg 31; Brakel; 33034; Germania