  This paper presents a new way to study registration based trackers by
decomposing them into three constituent sub modules: appearance model, state
space model and search method. It is often the case that when a new tracker is
introduced in literature, it only contributes to one or two of these sub
modules while using existing methods for the rest. Since these are often
selected arbitrarily by the authors, they may not be optimal for the new
method. In such cases, our breakdown can help to experimentally find the best
combination of methods for these sub modules while also providing a framework
within which the contributions of the new tracker can be clearly demarcated and
thus studied better. We show how existing trackers can be broken down using the
suggested methodology and compare the performance of the default configuration
chosen by the authors against other possible combinations to demonstrate the
new insights that can be gained by such an approach. We also present an open
source system that provides a convenient interface to plug in a new method for
any sub module and test it against all possible combinations of methods for the
other two sub modules while also serving as a fast and efficient solution for
practical tracking requirements.

Computer Vision and Pattern Recognition