Yazar
Topçu, O., Orguner, U., Alatan, A. A., Ercan, Ali Özer
Basım Tarihi
2014
Basım Yeri
-
IEEE
Konu
Visual tracking, Rao-Blackwellization, Marginalization, Occlusion, Particle filter, Multi-camera
Tür
Belge
Dil
Türkçe
Dijital
Evet
Yazma
Hayır
Kütüphane
Özyeğin Üniversitesi
Demirbaş Numarası
978-1-4799-4874-1
Kayıt Numarası
a9d56609-4892-4c1a-8396-13a1062bb3d5
Lokasyon
Electrical & Electronics Engineering
Tarih
2014
Notlar
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin
Visual tracking has an important place among computer vision applications. Visual tracking with particle filters is a well-known methodology. The performance of particle filters is dependent on efficient sampling of the state space, which in turn, is dependent on number of particles. In this paper, Rao-Blackwell technique is applied to particle filters to improve sampling efficiency. Both algorithms are applied to people tracking problem. Under the same circumstances, the resulting algorithm is demonstrated to perform better than the original algorithm via experiments on the PETS2009 benchmark dataset.
DOI
10.1109/SIU.2014.6830318
