@article{(Open Science Index):https://publications.waset.org/pdf/1982,
	  title     = {Using PFA in Feature Analysis and Selection for H.264 Adaptation},
	  author    = {Nora A. Naguib and  Ahmed E. Hussein and  Hesham A. Keshk and  Mohamed I. El-Adawy},
	  country	= {},
	  institution	= {},
	  abstract     = {Classification of video sequences based on their contents is a vital process for adaptation techniques. It helps decide which adaptation technique best fits the resource reduction requested by the client. In this paper we used the principal feature analysis algorithm to select a reduced subset of video features. The main idea is to select only one feature from each class based on the similarities between the features within that class. Our results showed that using this feature reduction technique the source video features can be completely omitted from future classification of video sequences.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {3},
	  number    = {6},
	  year      = {2009},
	  pages     = {1643 - 1645},
	  ee        = {https://publications.waset.org/pdf/1982},
	  url   	= {https://publications.waset.org/vol/30},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 30, 2009},
	}