@article{(Open Science Index):https://publications.waset.org/pdf/13361, title = {Video Classification by Partitioned Frequency Spectra of Repeating Movements}, author = {Kahraman Ayyildiz and Stefan Conrad}, country = {}, institution = {}, abstract = {In this paper we present a system for classifying videos by frequency spectra. Many videos contain activities with repeating movements. Sports videos, home improvement videos, or videos showing mechanical motion are some example areas. Motion of these areas usually repeats with a certain main frequency and several side frequencies. Transforming repeating motion to its frequency domain via FFT reveals these frequencies. Average amplitudes of frequency intervals can be seen as features of cyclic motion. Hence determining these features can help to classify videos with repeating movements. In this paper we explain how to compute frequency spectra for video clips and how to use them for classifying. Our approach utilizes series of image moments as a function. This function again is transformed into its frequency domain.}, journal = {International Journal of Computer and Information Engineering}, volume = {6}, number = {4}, year = {2012}, pages = {445 - 450}, ee = {https://publications.waset.org/pdf/13361}, url = {https://publications.waset.org/vol/64}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 64, 2012}, }