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KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker KLT: An Implementation of the

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<h2> Chapter 1: Introduction </h2>

KLT has been designed to be easy to use.  It should take no more than
a few minutes to learn how to select and track features, and store 
and use the results.  For those who wish to maximize performance,
however, the program allows the flexibility of tweaking nearly every
parameter that governs the computation, and it includes several 
methods to improve speed. <p>

This manual guides the user, in a tutorial fashion, through the
essentials of KLT.  Chapter 2 contains all that is needed to select
good features, track them from one image to the next, and write the
results.  When features are lost (due to a large residue, drifting out 
of bounds, etc.), they can be replaced
by finding features in the new image, a process which is described in 
Chapter 3.  Chapter 4 explains a technique for speeding up the computation
in the case of tracking through an image sequence.  Chapter 5 describes
an extension allowing the features from multiple frames to be stored
in one data structure, which can then be saved to a file.  Chapter
6 shows how to recall this structure and extract features from it.
Finally, Chapter 7 shows how to customize the tracker by 
manually setting the various parameters. <p>

Most of these chapters contain example code, which is also provided with 
the distribution of KLT.  

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