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Domain Transfer for Person Re-identification
| Citations: | 4 - 3 self |
BibTeX
@MISC{Layne_domaintransfer,
author = {Ryan Layne and Timothy M. Hospedales and Shaogang Gong},
title = {Domain Transfer for Person Re-identification},
year = {}
}
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Abstract
Automatic person re-identification in is a crucial capability underpinning many applications in public space video surveillance. It is challenging due to intra-class variation in person appearance when observed in different views, together with limited inter-class variability. Various recent approaches have made great progress in re-identification performance using discriminative learning techniques. However, these approaches are fundamentally limited by the requirement of extensive annotated training data for every pair of views. For practical re-identification, this is an unreasonable assumption, as annotating extensive volumes of data for every pair of cameras to be re-identified may be impossible or prohibitively expensive. In this paper we move toward relaxing this strong assumption by investigating flexible multi-source transfer of re-identification models across camera pairs. Specifically, we show how to leverage prior re-identification models learned for a set of source view pairs (domains), and flexibly combine these to obtain good re-identification performance in a target view pair (domain) with greatly reduced training data requirements in the target domain.
Keyphrases
person re-identification domain transfer many application camera pair flexible multi-source transfer intra-class variation various recent approach great progress extensive annotated training data good re-identification performance limited inter-class variability crucial capability target domain automatic person re-identification re-identification model practical re-identification discriminative learning technique training data requirement person appearance different view target view pair strong assumption unreasonable assumption public space video surveillance re-identification performance extensive volume source view pair prior re-identification model
