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Type: Journal article
Title: Tracking people across disjoint camera views by an illumination-tolerant appearance representation
Author: Madden, C.
Cheng, E.
Picardi, M.
Citation: Machine Vision and Applications: an international journal, 2007; 18(3-4):233-247
Publisher: Springer-Verlag
Issue Date: 2007
ISSN: 0932-8092
Statement of
Christopher Madden, Eric Dahai Cheng and Massimo Piccardi
Abstract: Tracking single individuals as they move across disjoint camera views is a challenging task since their appearance may vary significantly between views. Major changes in appearance are due to different and varying illumination conditions and the deformable geometry of people. These effects are hard to estimate and take into account in real-life applications. Thus, in this paper we propose an illumination-tolerant appearance representation, which is capable of coping with the typical illumination changes occurring in surveillance scenarios. The appearance representation is based on an online k-means colour clustering algorithm, a data-adaptive intensity transformation and the incremental use of frames. A similarity measurement is also introduced to compare the appearance representations of any two arbitrary individuals. Post-matching integration of the matching decision along the individuals‘ tracks is performed in order to improve reliability and robustness of matching. Once matching is provided for any two views of a single individual, its tracking across disjoint cameras derives straightforwardly. Experimental results presented in this paper from a real surveillance camera network show the effectiveness of the proposed method.
Keywords: Tracking
Disjoint camera views
Colour histograms
Online k-means clustering
Object similarity measurement
DOI: 10.1007/s00138-007-0070-6
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Appears in Collections:Aurora harvest
Computer Science publications

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