State of the Art in Face Recognition
by Julio Ponce, Adem Karahoca
Publisher: IN-TECH 2009
Number of pages: 436
Nearest feature classification for face recognition, subspace methods for face recognition, a multi-stage classifier for face recognition undertaken by coarse-to-fine strategy, PCA-ANN face recognition system based on photometric normalization techniques, online incremental face recognition system using eigenface feature and neural classifier, and more.
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by David Marshall - 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.
by Dana H. Ballard, Christopher M. Brown - Prentice Hall
The book on computer vision - the construction of explicit, meaningful descriptions of physical objects from images. Parts of the book assume some mathematical and computing background, but mainly mathematical rigor takes a backseat to concepts.
by Rong-Fong Fung - InTech
This is a book about how to employ the vision theory in the market conditions for students or researchers who want to realize the technique of machine vision. The book consists of 10 chapters on different fields about vision applications.
by Scott Krig - Springer
Provides an extensive survey of over 100 machine vision methods, with a detailed taxonomy for local, regional and global features. It provides background to develop intuition about why interest point detectors and feature descriptors actually work.