Video activity analysis based on 3D wavelet statistical properties

Authors:
M. Omidyeganeh;S. Ghaemmaghami;H. Khalilain
Affiliations:
Electrical Engineering Department and Advanced Information & Communication Technology Center;Electrical Engineering Department and Electronics Research Center, Sharif University of Technology;Electrical Engineering Department and Electronics Research Center, Sharif University of Technology
Venue:
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
Year:
2009

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Abstract

A video activity analysis is presented based on 3D wavelet transform. Marginal and joint statistics as well as mutual information estimates are extracted. Marginal histograms are approximated by Generalized Gaussian Density (GGD) functions. The mutual information between coefficients -as a quantitative estimate of joint statistics- decreases when the activity in the video increases. The relationship between kurtosis graphs, extracted from j oint distributions and video activity, is deduced. Results show that the type of activity in the video can be figured out from Kurtosis curves. The GGD and the Kullback-Leibler distance (KLD) are used to retrieve and locate 96% of videos properly.