Scholarly Research Excellence
%0 Journal Article
%A Kahraman Ayyildiz and  Stefan Conrad
%D 2012 
%J  International Journal of Computer, Electrical, Automation, Control and Information Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 67, 2012
%T Analyzing Transformation of 1D-Functions for Frequency Domain based Video Classification
%V 67
%X In this paper we illuminate a frequency domain based
classification method for video scenes. Videos from certain topical
areas often contain activities with repeating movements. Sports
videos, home improvement videos, or videos showing mechanical
motion are some example areas. Assessing main and side frequencies
of each repeating movement gives rise to the motion type. We
obtain the frequency domain by transforming spatio-temporal motion
trajectories. Further on we explain how to compute frequency features
for video clips and how to use them for classifying. The focus of
the experimental phase is on transforms utilized for our system.
By comparing various transforms, experiments show the optimal
transform for a motion frequency based approach.
%P 900 - 906