Person Re-Identification by Iterative Re-Weighted Sparse Ranking
In this paper we introduce a method for person re-identification based on discriminative, sparse basis expansions of targets in terms of a labeled gallery of known individuals. We propose an iterative extension to sparse discriminative classifiers capable of ranking many candidate targets. The appro...
Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 37(2015), 8 vom: 30. Aug., Seite 1629-42 |
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Weitere Verfasser: | , , |
Format: | Online-Aufsatz |
Sprache: | English |
Veröffentlicht: |
2015
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Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
Zusammenfassung: | In this paper we introduce a method for person re-identification based on discriminative, sparse basis expansions of targets in terms of a labeled gallery of known individuals. We propose an iterative extension to sparse discriminative classifiers capable of ranking many candidate targets. The approach makes use of soft- and hard- re-weighting to redistribute energy among the most relevant contributing elements and to ensure that the best candidates are ranked at each iteration. Our approach also leverages a novel visual descriptor which we show to be discriminative while remaining robust to pose and illumination variations. An extensive comparative evaluation is given demonstrating that our approach achieves state-of-the-art performance on single- and multi-shot person re-identification scenarios on the VIPeR, i-LIDS, ETHZ, and CAVIAR4REID datasets. The combination of our descriptor and iterative sparse basis expansion improves state-of-the-art rank-1 performance by six percentage points on VIPeR and by 20 on CAVIAR4REID compared to other methods with a single gallery image per person. With multiple gallery and probe images per person our approach improves by 17 percentage points the state-of-the-art on i-LIDS and by 72 on CAVIAR4REID at rank-1. The approach is also quite efficient, capable of single-shot person re-identification over galleries containing hundreds of individuals at about 30 re-identifications per second |
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Beschreibung: | Date Completed 27.05.2016 Date Revised 10.09.2015 published: Print Citation Status MEDLINE |
ISSN: | 1939-3539 |
DOI: | 10.1109/TPAMI.2014.2369055 |