Abstract
A key criticism in the experimental aspect in computer vision is
that there are many reported experiments which illustrate results on
only a few images and many experiments done all under essentially the
same conditions. Such experiments are not sufficient. The author argues
that the most informative kinds of experiments should state the set of
controlled conditions under which a vision algorithm can be utilized and
under which the vision algorithm performance exceeds some given
specification. The planning document which describes the design for
these experiments is called the experimental protocol. The specific
elements of such a protocol are reviewed, stressing that the
experimental data analysis plan must state how the hypothesis that the
algorithm meets the specified requirement will be tested. The plan must
be supported by theoretically developed statistical analysis which shows
that an experiment carried out according to the experimental design and
analyzed according to the data analysis plan will produce a statistical
test itself having a given accuracy
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