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Preface xix

has been driven by several trends: Computers and imaging systems have become
very cheap. Not all that long ago, it took tens of thousands of dollars to get good
digital color images; now it takes a few hundred at most. Not all that long ago, a
color printer was something one found in few, if any, research labs; now they are
in many homes. This means it is easier to do research. It also means that there
are many people with problems to which the methods of computer vision apply.
For example, people would like to organize their collections of photographs, make
3D models of the world around them, and manage and edit collections of videos.
Our understanding of the basic geometry and physics underlying vision and, more
important, what to do about it, has improved significantly. We are beginning to be
able to solve problems that lots of people care about, but none of the hard problems
have been solved, and there are plenty of easy ones that have not been solved either
(to keep one intellectually fit while trying to solve hard problems). It is a great
time to be studying this subject.

What Is in this Book
This book covers what we feel a computer vision professional ought to know. How-
ever, it is addressed to a wider audience. We hope that those engaged in compu-
tational geometry, computer graphics, image processing, imaging in general, and
robotics will find it an informative reference. We have tried to make the book
accessible to senior undergraduates or graduate students with a passing interest
in vision. Each chapter covers a different part of the subject, and, as a glance at
Table 1 will confirm, chapters are relatively independent. This means that one can
dip into the book as well as read it from cover to cover. Generally, we have tried to
make chapters run from easy material at the start to more arcane matters at the
end. Each chapter has brief notes at the end, containing historical material and
assorted opinions. We have tried to produce a book that describes ideas that are
useful, or likely to be so in the future. We have put emphasis on understanding the
basic geometry and physics of imaging, but have tried to link this with actual ap-
plications. In general, this book reflects the enormous recent influence of geometry
and various forms of applied statistics on computer vision.

Reading this Book
A reader who goes from cover to cover will hopefully be well informed, if exhausted;
there is too much in this book to cover in a one-semester class. Of course, prospec-
tive (or active) computer vision professionals should read every word, do all the
exercises, and report any bugs found for the third edition (of which it is probably a
good idea to plan on buying a copy!). Although the study of computer vision does
not require deep mathematics, it does require facility with a lot of different math-
ematical ideas. We have tried to make the book self-contained, in the sense that
readers with the level of mathematical sophistication of an engineering senior should
be comfortable with the material of the book and should not need to refer to other
texts. We have also tried to keep the mathematics to the necessary minimum—after
all, this book is about computer vision, not applied mathematics—and have chosen
to insert what mathematics we have kept in the main chapter bodies instead of a
separate appendix.