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Preface xxviii

TABLE 6: A syllabus for students who have a strong interest in applied mathematics,
electrical engineering, or physics.
Week Chapter Sections Key topics
1 1, 2 all; 2.1–2.4 cameras, shading
2 3 all color
3 4 all linear filters
4 5 all building local features
5 6 all texture
6 7 all stereopsis
7 8 all structure from motion with perspective cameras
8 9 all segmentation by clustering pixels
9 10 all fitting models
10 11 11.1–11.3 simple tracking strategies, tracking by matching,
Kalman filters, data association
11 12 all registration
12 15 all classification
13 16 all classifying images
14 17 all detection
15 choice all one of chapters 14, 19, 20, 21

PROGRAMMING ASSIGNMENTS AND RESOURCES
The programming assignments given throughout this book sometimes require rou-
tines for numerical linear algebra, singular value decomposition, and linear and
nonlinear least squares. An extensive set of such routines is available in MATLAB
as well as in public-domain libraries such as LINPACK, LAPACK, and MINPACK,
which can be downloaded from the Netlib repository (http://www.netlib.org/).
In the text, we offer extensive pointers to software published on the Web and to
datasets published on the Web. OpenCV is an important open-source package of
computer vision routines (see Bradski and Kaehler (2008)).