Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81702
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dc.contributor.authorZhou, Zhien
dc.contributor.authorWang, Yueen
dc.contributor.authorTeoh, Eam Khwangen
dc.contributor.editorJawahar, C. V.en
dc.contributor.editorShan, Shiguangen
dc.date.accessioned2016-01-11T08:23:12Zen
dc.date.accessioned2019-12-06T14:36:26Z-
dc.date.available2016-01-11T08:23:12Zen
dc.date.available2019-12-06T14:36:26Z-
dc.date.issued2014en
dc.identifier.citationZhou, 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.en
dc.identifier.urihttps://hdl.handle.net/10356/81702-
dc.description.abstractPeople 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.en
dc.format.extent32 p.en
dc.language.isoenen
dc.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].en
dc.subjectPeople re-identificationen
dc.subjectHuman appearance modelen
dc.subjectSemantic featuresen
dc.subjectSoft-biometricen
dc.subjectSurveillanceen
dc.titleA framework for semantic people description in multi-camera surveillance systemsen
dc.typeConference Paperen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.contributor.conferenceLecture Notes in Computer Scienceen
dc.identifier.doi10.1007/978-3-319-16634-6en
dc.description.versionAccepted versionen
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