Publication:
Estimating body related soft biometric traits in video frames

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dc.citedby9
dc.contributor.authorArigbabu O.A.en_US
dc.contributor.authorAhmad S.M.S.en_US
dc.contributor.authorAdnan W.A.W.en_US
dc.contributor.authorYussof S.en_US
dc.contributor.authorIranmanesh V.en_US
dc.contributor.authorMalallah F.L.en_US
dc.contributor.authorid56047591000en_US
dc.contributor.authorid24721182400en_US
dc.contributor.authorid6506665562en_US
dc.contributor.authorid16023225600en_US
dc.contributor.authorid56047920000en_US
dc.contributor.authorid56102103900en_US
dc.date.accessioned2023-05-16T02:47:09Z
dc.date.available2023-05-16T02:47:09Z
dc.date.issued2014
dc.description.abstractSoft biometrics can be used as a prescreening filter, either by using single trait or by combining several traits to aid the performance of recognition systems in an unobtrusive way. In many practical visual surveillance scenarios, facial information becomes difficult to be effectively constructed due to several varying challenges. However, from distance the visual appearance of an object can be efficiently inferred, thereby providing the possibility of estimating body related information. This paper presents an approach for estimating body related soft biometrics; specifically we propose a new approach based on body measurement and artificial neural network for predicting body weight of subjects and incorporate the existing technique on single view metrology for height estimation in videos with low frame rate. Our evaluation on 1120 frame sets of 80 subjects from a newly compiled dataset shows that the mentioned soft biometric information of human subjects can be adequately predicted from set of frames. © 2014 Olasimbo Ayodeji Arigbabu et al.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo460973
dc.identifier.doi10.1155/2014/460973
dc.identifier.scopus2-s2.0-84904682815
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84904682815&doi=10.1155%2f2014%2f460973&partnerID=40&md5=dcf6e638ea6aa6b464adf10d8acba5fb
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22073
dc.identifier.volume2014
dc.publisherHindawi Publishing Corporationen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleScientific World Journal
dc.titleEstimating body related soft biometric traits in video framesen_US
dc.typeArticleen_US
dspace.entity.typePublication
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