Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81702
Title: A framework for semantic people description in multi-camera surveillance systems
Authors: Zhou, Zhi
Wang, Yue
Teoh, Eam Khwang
Keywords: People re-identification
Human appearance model
Semantic features
Soft-biometric
Surveillance
Issue Date: 2014
Source: Zhou, Z., Wang, Y., & Teoh, E. K. (2015). A framework for semantic people description in multi-camera surveillance systems. Lecture Notes in Computer Science, 9010, 1-26.
Abstract: People re-identification has been a very active research topic recently in computer vision. It is an important application in surveillance systems with disjoint cameras. In this paper, a framework is proposed to extract descriptors of people in videos, which are based on soft-biometric traits and can be further used for people reidentification or other applications. Soft-biometric based description is more invariant to changing factors than directly using low level features such as color and texture. The ensemble of a set of soft-biometric traits can achieve good performance in people re-identification. In the proposed method, the body of detected people is divided into three parts and the selected soft-biometric traits are extracted from each part. All traits are then combined to form the final descriptor, and people reidentification is performed based on the descriptor and Nearest Neighbor (NN) matching strategy. The experiments are carried out on SAIVT-SoftBio database which consists of videos from disjoint surveillance cameras. An Open ID recognition problem is also evaluated for the proposed method. Comparisons with some state-of-the-art methods are provided as well. The experiment results show the good performance of the proposed framework.
URI: https://hdl.handle.net/10356/81702
http://hdl.handle.net/10220/39653
DOI: 10.1007/978-3-319-16634-6
Rights: © 2015 Springer International Publishing Switzerland. This is the author created version of a work that has been peer reviewed and accepted for publication by Computer Vision - ACCV 2014 Workshops, Lecture Notes in Computer Science, Springer. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1007/978-3-319-16634-6].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

Files in This Item:
File Description SizeFormat 
A framework for semantic people description.pdf11.38 MBAdobe PDFThumbnail
View/Open

Page view(s) 50

227
checked on Sep 30, 2020

Download(s) 50

140
checked on Sep 30, 2020

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.