Next Article in Journal
Estimating Full Regional Skeletal Muscle Fibre Orientation from B-Mode Ultrasound Images Using Convolutional, Residual, and Deconvolutional Neural Networks
Previous Article in Journal
A New Binarization Algorithm for Historical Documents
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
J. Imaging 2018, 4(2), 28; https://doi.org/10.3390/jimaging4020028

Exploiting Multiple Detections for Person Re-Identification

Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
*
Author to whom correspondence should be addressed.
Received: 18 November 2017 / Revised: 11 January 2018 / Accepted: 11 January 2018 / Published: 23 January 2018
Full-Text   |   PDF [1859 KB, uploaded 23 January 2018]   |  

Abstract

Re-identification systems aim at recognizing the same individuals in multiple cameras, and one of the most relevant problems is that the appearance of same individual varies across cameras due to illumination and viewpoint changes. This paper proposes the use of cumulative weighted brightness transfer functions (CWBTFs) to model these appearance variations. Different from recently proposed methods which only consider pairs of images to learn a brightness transfer function, we exploit such a multiple-frame-based learning approach that leverages consecutive detections of each individual to transfer the appearance. We first present a CWBTF framework for the task of transforming appearance from one camera to another. We then present a re-identification framework where we segment the pedestrian images into meaningful parts and extract features from such parts, as well as from the whole body. Jointly, both of these frameworks contribute to model the appearance variations more robustly. We tested our approach on standard multi-camera surveillance datasets, showing consistent and significant improvements over existing methods on three different datasets without any other additional cost. Our approach is general and can be applied to any appearance-based method. View Full-Text
Keywords: video surveillance; appearance-based re-identification; brightness transfer function; segmentation video surveillance; appearance-based re-identification; brightness transfer function; segmentation
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Bhuiyan, A.; Perina, A.; Murino, V. Exploiting Multiple Detections for Person Re-Identification. J. Imaging 2018, 4, 28.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
J. Imaging EISSN 2313-433X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top