Paper
19 February 2013 Target re-identification in low-quality camera networks
Author Affiliations +
Proceedings Volume 8655, Image Processing: Algorithms and Systems XI; 865502 (2013) https://doi.org/10.1117/12.2004470
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
Abstract
Person re-identification through a camera network deals with finding a correct link between consecutive observations of the same target among different cameras in order to choose the most probable correspondence among a set of possible matches. This task is particularly challenging in presence of low-resolution camera networks. In this work, a method for people re-identification in a framework of low-resolution camera network is presented. The proposed approach can be divided in two parts. First, the illumination changes of a target while crossing the network is analyzed. The color structure is evaluated using a novel color descriptor, the Color Structure Descriptor, which describes the differences of dominant colors between two regions of interest. Afterwards, a new pruning system for the links, the Target Color Structure is proposed. Results shows that the improvements achieved applying Target Color Structure control are up to 4% for the top rank and up to 16% considering the first eleven more similar candidates.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Federica Battisti, Marco Carli, Giovanna Farinella, and Alessandro Neri "Target re-identification in low-quality camera networks", Proc. SPIE 8655, Image Processing: Algorithms and Systems XI, 865502 (19 February 2013); https://doi.org/10.1117/12.2004470
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Cited by 1 scholarly publication.
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KEYWORDS
Cameras

RGB color model

Video surveillance

Video

Detection and tracking algorithms

Head

Imaging systems

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