Dynamic Vision: From Images to Face Recognition (Image Processing)

Rating:
Summary: dynamic vision:from images to face recognition
Review: Reviewer: Ph.D. in Applied Mathematics

When you pick this book up, it looks like a very promising exposition of computer face recognition. However, the best part of this book is its attractive dust cover. Large parts of the book are purely descriptive discussion. At the beginning, this discussion provides an overview of the challenges in this area, as well as many of the buzz words that might be useful for writing an inroduction to a proposal. However, most of the descriptive discussion is somewhat vague and lacks any real insight into what the problems are or how one may go about solving them. One hopes that when the writers get to quantifying things with some mathematics, things will get better, but they don't.

The first mathematical descriptions were so fuzzy and poorly motivated that I was discourage from reading farther. The authors throw around probabilities w/o clearly defining what they mean, variables that tax the reader to supply an explanation of what they represent, and changes in formalism that are just confusing. Quite possibly they know what they are talking about, but they owe the reader a much bettter explanation of what they are trying to say.

From a cursory review of the remainder of the book, it appeares to be a collection of various equations w/o much of an explanation on how these would be applied to the problem of face recognition.

After reading this book, you may be more familiar with the jargon of the subject, but not much closer to understanding face recognition

Rating:
Summary: A very good introductory text
Review: The book provides an excellent introduction to many areas of modern computer vision and machine learning. Although the book is primarily concerned with high-level vision problems such as face recognition, it provides a valuable compendium on a variety of algorithms and statistical techniques which have come into vogue over the last few years.
Complex topics such as statistical learning theory are explained very clearly and concisely with just the right amount of mathematics. The mathematical descriptions are of a kind familiar to anyone with a good science or engineering background, i.e. they are designed to provide insight and formal structure rather than endless proofs of pointless theorems.
I particularly liked the way in which the authors clearly formulate and motivate the key problems before presenting and comparing different solutions. Although somewhat expensive, this book is an excellent introduction and reference for anyone seriously interested in the subject.