Title

Consistent labeling of tracked objects in multiple cameras with overlapping fields of view

Authors

Authors

S. Khan;M. Shah

Comments

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Abbreviated Journal Title

IEEE Trans. Pattern Anal. Mach. Intell.

Keywords

tracking; multiple cameras; multiperspective video; surveillance; camera; handoff; sensor fusion; Computer Science, Artificial Intelligence; Engineering, Electrical &; Electronic

Abstract

In this paper, we address the issue of tracking moving objects in an environment covered by multiple uncalibrated cameras with overlapping fields of view, typical of most surveillance setups. In such a scenario, it is essential to establish correspondence between tracks of the same object, seen in different cameras, to recover complete information about the object. We call this the problem of consistent labeling of objects when seen in multiple cameras. We employ a novel approach of finding the limits of field of view (FOV) of each camera as visible in the other cameras. We show that, if the FOV lines are known, it is possible to disambiguate between multiple possibilities for correspondence. We present a method to automatically recover these lines by observing motion in the environment. Furthermore, once these lines are initialized, the homography between the views can also be recovered. We present results on indoor and outdoor sequences containing persons and vehicles.

Journal Title

Ieee Transactions on Pattern Analysis and Machine Intelligence

Volume

25

Issue/Number

10

Publication Date

1-1-2003

Document Type

Article

Language

English

First Page

1355

Last Page

1360

WOS Identifier

WOS:000185460800018

ISSN

0162-8828

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