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CHENG et al.: CUSTOM PICTORIAL STRUCTURES FOR RE-IDENTIFICATION 1 Custom Pictorial Structures for Re-identification
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BibTeX
@MISC{Cheng_chenget,
author = {Dong Seon Cheng and Marco Cristani and Loris Bazzani and Vittorio Murino},
title = {CHENG et al.: CUSTOM PICTORIAL STRUCTURES FOR RE-IDENTIFICATION 1 Custom Pictorial Structures for Re-identification},
year = {}
}
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Abstract
We propose a novel methodology for re-identification, based on Pictorial Structures (PS). Whenever face or other biometric information is missing, humans recognize an individual by selectively focusing on the body parts, looking for part-to-part correspondences. We want to take inspiration from this strategy in a re-identification context, using PS to achieve this objective. For single image re-identification, we adopt PS to localize the parts, extract and match their descriptors. When multiple images of a single individual are available, we propose a new algorithm to customize the fit of PS on that specific person, leading to what we call a Custom Pictorial Structure (CPS). CPS learns the appearance of an individual, improving the localization of its parts, thus obtaining more reliable visual characteristics for re-identification. It is based on the statistical learning of pixel attributes collected through spatio-temporal reasoning. The use of PS and CPS leads to state-of-the-art results on all the available public benchmarks, and opens a fresh new direction for research on re-identification. 1
Keyphrases
custom pictorial structure custom pictorial structure re-identification new algorithm reliable visual characteristic single individual pixel attribute state-of-the-art result biometric information body part multiple image specific person fresh new direction part-to-part correspondence novel methodology pictorial structure re-identification context available public benchmark spatio-temporal reasoning statistical learning single image re-identification
