Person Re-Identification by Discriminative Selection in Video Ranking
- 27 January 2016
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Pattern Analysis and Machine Intelligence
- Vol. 38 (12), 2501-2514
- https://doi.org/10.1109/tpami.2016.2522418
Abstract
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.Keywords
Funding Information
- National Science and Technology (2013BAK02B04)
- Tsinghua Initiative Scientific Research (20141081253)
This publication has 49 references indexed in Scilit:
- On-the-fly feature importance mining for person re-identificationPattern Recognition, 2014
- Part-based spatio-temporal model for multi-person re-identificationPattern Recognition Letters, 2012
- A survey of vision-based methods for action representation, segmentation and recognitionComputer Vision and Image Understanding, 2011
- Person Re-identification by Descriptive and Discriminative ClassificationLecture Notes in Computer Science, 2011
- Gait recognition without subject cooperationPattern Recognition Letters, 2010
- Volumetric Features for Video Event DetectionInternational Journal of Computer Vision, 2009
- A survey on vision-based human action recognitionImage and Vision Computing, 2009
- Efficient algorithms for ranking with SVMsInformation Retrieval Journal, 2009
- On Space-Time Interest PointsInternational Journal of Computer Vision, 2005
- Full-body person recognition systemPattern Recognition, 2003