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Occlusion-aware 3D multiple object tracker with two cameras for visual surveillance

Title	Occlusion-aware 3D multiple object tracker with two cameras for visual surveillance
Author	Topçu, O., Alatan, A. A., Ercan, Ali Özer
Publication Date:	2014
Publication Place	- IEEE
Subject	Object tracking, Particle filtering (numerical methods), Probability, Video cameras, Video surveillance
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	978-1-4799-4871-0
Record ID	f1a16bc5-9157-45d7-8216-fccd8cfe23c2
Library Location	Electrical & Electronics Engineering
Date	2014
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	An occlusion-aware multiple deformable object tracker for visual surveillance from two cameras is presented. Each object is tracked by a separate particle filter tracker, which is initiated upon detection of a new person and terminated when s/he leaves the scene. Objects are considered as 3D points at their centre of masses as if their mass density is uniform. Point objects and corresponding silhouette centroids in two views together with the epipolar geometry they satisfy resulted in a practical tracking methodology. An occlusion filter is described, that provides the tracker filters conditional occlusion probabilities of the objects, given their estimated positions. Advances over the previous work; in the computation of conditional occlusion probabilities, in incorporation of these probabilities in the particle filter, and in maintaining tracking of separating objects after long periods of moving close-by, are presented on PETS 2006, PETS 2009 and EPFL datasets.
DOI	10.1109/AVSS.2014.6918644

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Özyeğin University

Occlusion-aware 3D multiple object tracker with two cameras for visual surveillance

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

Publication Date 2014

Publication Place - IEEE

Subject Object tracking, Particle filtering (numerical methods), Probability, Video cameras, Video surveillance

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 978-1-4799-4871-0

Record ID f1a16bc5-9157-45d7-8216-fccd8cfe23c2

Library Location Electrical & Electronics Engineering

Date 2014

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

Sample Text An occlusion-aware multiple deformable object tracker for visual surveillance from two cameras is presented. Each object is tracked by a separate particle filter tracker, which is initiated upon detection of a new person and terminated when s/he leaves the scene. Objects are considered as 3D points at their centre of masses as if their mass density is uniform. Point objects and corresponding silhouette centroids in two views together with the epipolar geometry they satisfy resulted in a practical tracking methodology. An occlusion filter is described, that provides the tracker filters conditional occlusion probabilities of the objects, given their estimated positions. Advances over the previous work; in the computation of conditional occlusion probabilities, in incorporation of these probabilities in the particle filter, and in maintaining tracking of separating objects after long periods of moving close-by, are presented on PETS 2006, PETS 2009 and EPFL datasets.

DOI 10.1109/AVSS.2014.6918644