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Human Re-identification using Colour and Texture Features.

Author(s)
RNewlin Shebiah Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi
S Arivazhagan Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi
Abstract
Human Re-Identification turns out to be the most fascinating and perplexing tasks in the domain of smart video surveillance in recent time. Re-Identification is crucial in establishing reliable tagging of person across multiple cameras or even within the same camera to re-establish detached or lost tracks. The challenge in Person Re-Identification lies due to the visual and spatio-temporal uncertainty in the appearance of the person's across multiple cameras. Here, a viewpoint invariant human re-identification framework with colour and texture features is proposed. The descriptor encodes the visual features of the human from the chromatic content described by colour statistical features, Local Binary histogram and Histogram of Gradients derived from wavelet transformed input image. Similarity measure is found by the Euclidean distance measured between the extracted feature descriptors from the non-overlapping cameras. From the experimental results it is observed that the proposed system significantly out performs state-of-the-art algorithms on the VIPeR Human Re-identification dataset.
Publication Details
Page(s) 27-30
DOI DOI not available
Published Journal: Pakistan Journal of Biotechnology, Volume: 15, Issue: S1, Year: 2018

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References
Burrus , G.R.A,H. Guo, 1993.Expansion of notes for the IEEE Society's tutorial program held in conjunction with the ICASSP (, -
Dalal N.,B.Triggs, 2005.Histograms of oriented gradients for human detection,IEEE Computer Society Conference on Computer Vision 886 893 -
Daubechies, 1988.Orthonormal bases for compactly supported Wavelets,Comm. Pure Applied Math 12 909 -996
Drimbarean , A.,P.F.Whelan, 2001.Experiments in colour texture analysis,Pattern Recognition Letters 22 1161 -1167
Farenzena , M.,L.Bazzani,A.Perina,V.Murino,M.Cristani, 2010.Person re-identification by symmetry-driven accumulation of local features,IEEE Conference on Computer Vision 2360 2367 -
Gheissari,T. B. Sebastian , P. H.,Tu , J.,Rittscher and R.,Hartley, 2006.Person Reidentification Using Spatiotemporal Appearance,In IEEE Conference on Computer Vision 1528 1535 -
GianfrancoDoretto,PeterTu,JensRittscher, 2011.Appearance-based person reidentification in camera networks: problem overview and current approaches,Journal of Ambient Intelligence and Humanized Computing 2 127 -151
Gray , D.,H.Tao, 2008.Viewpoint invariant pedestrian recognition with an ensemble of localized features,European Conference on Computer Vision 262 -
Gray , D.,Brennan , S.,H.Tao, 2007.Evaluating appearance models for recognition, reacquisition and tracking,Proc. IEEE Int'l Workshop on Performance Evaluation of Tracking and Surveillance -
Karthikeyan , M.V.,M.V.J.Martin,LeoManickam, 2017.A 128-bit secret key generation using unique ecg biosignal for medical data cryptography in lightweight wireless body area networks,Pak. J. Biotechnol 14 257 -264
Ma , B.,Y.Su,F.Jurie,British Machine Vision Association, 2012.BiCov: a novel image representation for person re-identification and face verifycation,In British Machine Vision Conference 11 -57
Madden , C.,M.Piccardi, 2007.Tracking people across disjoint camera views by an illumination-tolerant appearance representation,Machine Vision and Applications 18 233 -247
Mäenpää , T.,J. , Gustavsson, 2003.M. Pietikäinen, Multi-scale Binary Patterns for Texture Analysis, 2749 885 -892
Maenpaa , T., 2003.The Local Binary Pattern Approach to Texture Analysis-Extensions and, 42 47 -
Orwell , J.,P.Remagnino,G.A.Jones, 1999.Multiple camera color tracking,IEEE Workshop on Visual Surveillance -
Park , U.,A.Jain,I. Kitahara,N.Hagita, 2006.ViSE: Visual Search Engine Using Multiple Networked Cameras,International Conference on Pattern Recognition Pp 1204 1207 -
Raflaa S.,H.Hussian, 2017.Molecular detection of entamoeba gingivalis using polymerase chain reaction,Pak. J. Biotechnol 14 351 -354
RenX.M.,WangX.F.,Y. Zhao,,JoK.H.,Gromiha M.M., 2012.(eds) Intelligent Computing Theories and Applications, 7390 -
Strang,T. Nguyen , Wavelets and Filter,Banks, 1996., -
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