Logo

Computer Vision: Models, Learning, and Inference

Large book cover: Computer Vision: Models, Learning, and Inference

Computer Vision: Models, Learning, and Inference
by

Publisher: Cambridge University Press
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.

Home page url

Download or read it online for free here:
Download link
(105MB, PDF)

Similar books

Book cover: Vision SystemsVision Systems
by - Cardiff School of Computer Science
From the table of contents: Image Acquisition: 2D Image Input, 3D imaging; Image processing: Fourier Methods, Smoothing Noise; Edge Detection; Edge Linking; Segmentation; Line Labelling; Relaxation Labelling; Optical Flow; Object Recognition.
(14482 views)
Book cover: Modern Robotics with OpenCVModern Robotics with OpenCV
by - Science Publishing Group
This book is written to provide an introduction to intelligent robotics using OpenCV. It is intended for a first course in robot vision and covers modeling and implementation of intelligent robot. Written for student and hobbyist.
(9257 views)
Book cover: Machine Interpretation of Line DrawingsMachine Interpretation of Line Drawings
by - The MIT Press
The book on computer vision which solves the problem of the interpretation of line drawings and answers many other questions regarding the errors in the placement of lines in the images. Sugihara presents a mechanism that mimics human perception.
(16609 views)
Book cover: Stereo VisionStereo Vision
by - InTech
The book comprehensively covers almost all aspects of stereo vision. In addition reader can find topics from defining knowledge gaps to the state of the art algorithms as well as current application trends of stereo vision.
(15040 views)