| dc.contributor.author | Wang, T | en_US |
| dc.contributor.author | Gong, S | en_US |
| dc.contributor.author | Zhu, X | en_US |
| dc.contributor.author | Wang, S | en_US |
| dc.date.accessioned | 2016-03-11T15:41:24Z | |
| dc.date.available | 2016-01-17 | en_US |
| dc.date.issued | 2016-12 | en_US |
| dc.date.submitted | 2016-02-16T19:14:30.837Z | |
| dc.identifier.issn | 0162-8828 | en_US |
| dc.identifier.uri | http://qmro.qmul.ac.uk/xmlui/handle/123456789/11432 | |
| dc.description | Current person re-identification (ReID) methods typically rely on single-frame imagery features, whilst ignoring space-time information from image sequences often available in the practical surveillance scenarios. Single-frame (single-shot) based visual appearance matching is inherently limited for person ReID in public spaces due to the challenging visual ambiguity and uncertainty arising from non-overlapping camera views where viewing condition changes can cause significant people appearance variations. In this work, we present a novel model to automatically select the most discriminative video fragments from noisy/incomplete image sequences of people from which reliable space-time and appearance features can be computed, whilst simultaneously learning a video ranking function for person ReID. Using the PRID2011, iLIDS-VID, and HDA+ image sequence datasets, we extensively conducted comparative evaluations to demonstrate the advantages of the proposed model over contemporary gait recognition, holistic image sequence matching and state-of-the-art single-/multi-shot ReID methods. | en_US |
| dc.format.extent | 2501 - 2514 | en_US |
| dc.relation.ispartof | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | en_US |
| dc.subject | Person re-identification | en_US |
| dc.subject | sequence matching | en_US |
| dc.subject | discriminative selection | en_US |
| dc.subject | multi-instance ranking | en_US |
| dc.subject | video ranking | en_US |
| dc.title | Person Re-Identification by Discriminative Selection in Video Ranking | en_US |
| dc.type | Article | |
| dc.rights.holder | 2016 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. | |
| dc.identifier.doi | 10.1109/TPAMI.2016.2522418 | en_US |
| pubs.author-url | http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000387984700012&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6a | en_US |
| pubs.issue | 12 | en_US |
| pubs.notes | Not known | en_US |
| pubs.publication-status | Published | en_US |
| pubs.volume | 38 | en_US |
| qmul.funder | Newton Advanced Fellowship: Person Re-Identification::Royal Society | en_US |
| qmul.funder | Newton Advanced Fellowship: Person Re-Identification::Royal Society | en_US |
