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Support vector machines based target tracking techniques [Destek vektör makineleri tabanlı hedef takip yöntemleri]

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Support vector machines based target tracking techniques.pdf (688.4Kb)
Date
2006
Author
Özer, Sedat
Cirpan, Hakan Ali
Kabaoǧlu, Nihat
Abstract
This paper addresses the problem of aplying powerful statistical pattern classification algorithms based on kernels to target tracking. Rather than directly adapting a recognizer we develop a localizer directly using the regression form of the Support Vector Machines (SVM). The proposed approach considers using dynamic model together as feature vectors and makes the hyperplane and the support vectors follow the changes in these features. The performance of the tracker is demostrated in a sensor network scenario with a moving target in a polynomial route. © 2006 IEEE.

Source

2006 IEEE 14th Signal Processing and Communications Applications Conference

Volume

2006

URI

https://hdl.handle.net/20.500.12469/1650
https://dx.doi.org/10.1109/SIU.2006.1659718

Collections

  • Araştırma Çıktıları / Scopus [1565]
  • Elektrik-Elektronik Mühendisliği / Electrical - Electronics Engineering [321]
  • Teknik Bilimler Meslek Yüksekokulu [6]

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