Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A complete person re-identification model using Kernel-PCA-based Gabor-filtered hybrid descriptors Subject The topic of the resource Deep learning; Distance metric learning; Kernel PCA; Pedestrian detection; Person re-identification; Spatial descriptor; Video surveillance Description An account of the resource Person re-identification is a challenging problem in computer vision. Lots of research interest is observed in this area over the past few years. A model for complete person re-identification can prove useful in this direction. Use of convolutional neural networks for pedestrian detection can improve the accuracy of detection to a larger extent. Deriving a descriptor which is invariant to the changes in the illumination, background and the pose can make the difference in the re-identification process. The predominant part of our work focuses on building a robust descriptor which can tackle such challenges. We have concentrated on building a descriptor by employing appearance-based features extracted both at local and global levels. Further, the dimensionality of the descriptor is reduced using kernel PCA. Distance metric learning algorithms are used to evaluate the descriptor on three major benchmark datasets. We propose a complete person re-identification system which involves both pedestrian detection and person re-identification. Major contributions of this work are to detect pedestrians from surveillance videos using CNN-based learning and to generate a kernel-PCA-based spatial descriptor and evaluate the descriptor using known distance metric learning methods on benchmark datasets. 2018, Springer-Verlag London Ltd., part of Springer Nature. Creator An entity primarily responsible for making the resource Sathish P.K.; Balaji S. Source A related resource from which the described resource is derived International Journal of Multimedia Information Retrieval, Vol-7, No. 4, pp. 221-229. Publisher An entity responsible for making the resource available Springer London Date A point or period of time associated with an event in the lifecycle of the resource 2018-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s13735-018-0153-3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s13735-018-0153-3</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044449643&amp;doi=10.1007%2Fs13735-018-0153-3&amp;partnerID=40&amp;md5=c81a84975f1d546ec3e0463f86712a65" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044449643&amp;doi=10.1007%2fs13735-018-0153-3&amp;partnerID=40&amp;md5=c81a84975f1d546ec3e0463f86712a65</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 21926611 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sathish P.K., Department of Computer Science and Engineering, Christ University, Bengaluru, 560074, India; Balaji S., Centre for Incubation, Innovation, Research and Consultancy, Jyothi Institute of Technology, Bengaluru, India