Kernel Subclass Support Vector Description for Face and Human Action Recognition

Vasileios Mygdalis, Alexandros Iosifidis, Anastasios Tefas, Ioannis Pitas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

4 Citations (Scopus)
251 Downloads (Pure)

Abstract

In this paper, we present the Kernel Subclass Support Vector Data Description classifier. We focus on face recognition and human action recognition applications, where we argue that sub-classes are formed within the training class. We modify the standard SVDD optimization problem, so that it exploits subclass information in its optimization process. We extend the proposed method to work in feature spaces of arbitrary dimensionality. We evaluate the proposed method in publicly available face recognition and human action recognition datasets. Experimental results have shown that increased performance can be obtained by employing the proposed method.
Original languageEnglish
Title of host publication2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE 2016)
Subtitle of host publicationProceedings of a meeting held 6-8 July 2016, Aalborg, Denmark
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages5
ISBN (Electronic)9781467389174
ISBN (Print)9781467389181
DOIs
Publication statusPublished - Aug 2016
EventInternational Workshop on Sensing, Processing and Learning for Intelligent Machines - Aalborg, Denmark
Duration: 6 Jul 20168 Jul 2016

Conference

ConferenceInternational Workshop on Sensing, Processing and Learning for Intelligent Machines
Abbreviated titleSPLINE
CountryDenmark
CityAalborg
Period6/07/168/07/16

Fingerprint Dive into the research topics of 'Kernel Subclass Support Vector Description for Face and Human Action Recognition'. Together they form a unique fingerprint.

Cite this