01938oam 2200433zu 450 991013913990332120241212215848.097814244780261424478022(CKB)2560000000009564(SSID)ssj0000452533(PQKBManifestationID)12173015(PQKBTitleCode)TC0000452533(PQKBWorkID)10471614(PQKB)10669627(NjHacI)992560000000009564(EXLCZ)99256000000000956420160829d2010 uy engur|||||||||||txtccr2010 IEEE Southwest Symposium on Image Analysis and Interpretation[Place of publication not identified]IEEE20101 online resourceBibliographic Level Mode of Issuance: Monograph9781424478019 1424478014 This 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.Image analysisCongressesImage analysis006.37ieeePQKBPROCEEDING99101391399033212010 IEEE Southwest Symposium on Image Analysis and Interpretation2498138UNINA