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100   $a20160829d2010      uy 
101 0 $aeng
135   $aur|||||||||||
181   $ctxt
182   $cc
183   $acr
200 10$a2010 IEEE Southwest Symposium on Image Analysis and Interpretation
210 31$a[Place of publication not identified]$cIEEE$d2010
215   $a1 online resource
300   $aBibliographic Level Mode of Issuance: Monograph
311 08$a9781424478019 
311 08$a1424478014 
330   $aThis paper presents a method, the snake particle filter (SPF), for tracking targets in video sequences. Manual or semi-automated solutions are both expensive and susceptible to error. In the SPF algorithm, automated tracking is accomplished by combining the particle filter with the snake. Here we employ the snake to establish the target shape, which is used to assign the weight for each particle in the particle filter. The snake provides a likelihood measure in the flexible particle filter framework that accommodates non-linear, non-Gaussian systems. Our results show that the SPF algorithm has an associated low RMSE value of approximately five pixels in the sequences tested for this study.
606   $aImage analysis$vCongresses
615  0$aImage analysis
676   $a006.37
702   $aieee
801  0$bPQKB
906   $aPROCEEDING
912   $a9910139139903321
996   $a2010 IEEE Southwest Symposium on Image Analysis and Interpretation$92498138
997   $aUNINA