  This paper adapts a popular image quality measure called structural
similarity for high precision registration based tracking while also
introducing a simpler and faster variant of the same. Further, these are
evaluated comprehensively against existing measures using a unified approach to
study registration based trackers that decomposes them into three constituent
sub modules - appearance model, state space model and search method. Several
popular trackers in literature are broken down using this method so that their
contributions - as of this paper - are shown to be limited to only one or two
of these submodules. An open source tracking framework is made available that
follows this decomposition closely through extensive use of generic
programming. It is used to perform all experiments on four publicly available
datasets so the results are easily reproducible. This framework provides a
convenient interface to plug in a new method for any sub module and combine it
with existing methods for the other two. It can also serve as a fast and
flexible solution for practical tracking needs due to its highly efficient
implementation.
