Computer Vision: Models, Learning, and Inference
by Simon J.D. Prince
Publisher: Cambridge University Press 2012
ISBN/ASIN: 1107011795
ISBN-13: 9781107011793
Number of pages: 665
Description:
This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data.
Download or read it online for free here:
Download link
(105MB, PDF)
Similar books
Pattern Recognitionby Peng-Yeng Yin - IN-TECH
The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms.
(10098 views)
Advances in Stereo Visionby Jose R.A. Torreao - InTech
In this small book the authors have attempted to present a limited but relevant sample of the work being carried out in stereo vision, covering significant aspects both from the applied and from the theoretical standpoints.
(5216 views)
State of the Art in Face Recognitionby Julio Ponce, Adem Karahoca - IN-TECH
Nearest feature classification for face recognition, subspace methods, a multi-stage classifier for face recognition undertaken by coarse-to-fine strategy, PCA-ANN face recognition system based on photometric normalization techniques, etc.
(6894 views)
Face Recognitionby Kresimir Delac, Mislav Grgic - InTech
This book will serve as a handbook for students, researchers and practitioners in the area of automatic (computer) face recognition and inspire some future research ideas by identifying potential research directions within the area.
(10677 views)