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

    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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