Görünüş temelli̇ örtüşme gözeten 3D nesne taki̇bi̇

Name: Görünüş temelli̇ örtüşme gözeten 3D nesne taki̇bi̇
Author: Topçu, O., Ercan, Ali Özer, Alatan, A.

İsim	Görünüş temelli̇ örtüşme gözeten 3D nesne taki̇bi̇
Yazar	Topçu, O., Ercan, Ali Özer, Alatan, A.
Basım Tarihi:	2012
Basım Yeri	- IEEE
Konu	Computer vision, Particle filtering (numerical methods), Target tracking
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-1-4673-0054-4
Kayıt Numarası	e72683a2-d346-489a-a724-9da24498d752
Lokasyon	Electrical & Electronics Engineering
Tarih	2012
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	Object tracking is an important element of computer vision algorithms. This problem is difficult due to occlusion, illumination changes and shadows. We propose an appearance based occlusion-aware method for object tracking. Proposed method is based on particle filter tracking in a multi-camera environment. In this method, observations involving both position and appearance information are evaluated depending on whether the corresponding objects are involved in occlusion or not. Tracking is done using state vector in 3D coordinates and probabilities that objects are occluded is estimated to elevate tracking performance. Particles are graded according to their positions and appearances by taking occlusions into account. Weighting particles in terms of position information allows particles to imitate object position and motion. Appearance information help recognize objects after occlusion and track objects when position information is not available. In case of occlusion, particles are weighted according to occlusion probability in order not to make them affected by possibly false measurements. Appearance information is updated by time to account for appearance changes. Appearance is not updated if the object is involved in occlusion. Experiments with PETS and EPFL datasets revealed the success of proposed method and that our method can be applied to different camera configurations.
DOI	10.1109/SIU.2012.6204775

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Görünüş temelli̇ örtüşme gözeten 3D nesne taki̇bi̇

Yazar Topçu, O., Ercan, Ali Özer, Alatan, A.

Basım Tarihi 2012

Basım Yeri - IEEE

Konu Computer vision, Particle filtering (numerical methods), Target tracking

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-1-4673-0054-4

Kayıt Numarası e72683a2-d346-489a-a724-9da24498d752

Lokasyon Electrical & Electronics Engineering

Tarih 2012

Notlar Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Örnek Metin Object tracking is an important element of computer vision algorithms. This problem is difficult due to occlusion, illumination changes and shadows. We propose an appearance based occlusion-aware method for object tracking. Proposed method is based on particle filter tracking in a multi-camera environment. In this method, observations involving both position and appearance information are evaluated depending on whether the corresponding objects are involved in occlusion or not. Tracking is done using state vector in 3D coordinates and probabilities that objects are occluded is estimated to elevate tracking performance. Particles are graded according to their positions and appearances by taking occlusions into account. Weighting particles in terms of position information allows particles to imitate object position and motion. Appearance information help recognize objects after occlusion and track objects when position information is not available. In case of occlusion, particles are weighted according to occlusion probability in order not to make them affected by possibly false measurements. Appearance information is updated by time to account for appearance changes. Appearance is not updated if the object is involved in occlusion. Experiments with PETS and EPFL datasets revealed the success of proposed method and that our method can be applied to different camera configurations.

DOI 10.1109/SIU.2012.6204775