Micro-expression detection using integral projections

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dc.contributor.authorLu, Hua
dc.contributor.authorKpalma, Kidiyo
dc.contributor.authorRonsin, Joseph
dc.contributor.editorSkala, Václav
dc.date.accessioned2017-09-01T08:06:03Z
dc.date.available2017-09-01T08:06:03Z
dc.date.issued2017
dc.description.abstract-translatedAutomatic detection of micro-expression from a video is the first step in the micro-expression analysis. In this paper, we present a method addressing the micro-expression detection problem based on the differences in the Integral Projection (IP) of sequential frames. The method can detect the temporal location of the micro-expression. It involves an observation of the Chi-squared distance of the IP to measure the difference between frames. The main advantage of using IP for micro-expression detection is its low computation cost, which brings an important merit in real-time application. To evaluate our method, experiments are completed on two micro-expression databases namely CASME and CASME II. Results on these two datasets show that the proposed method obtains positive promising results with much less computation time against state-of-the-art methods.en
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationJournal of WSCG. 2017, vol. 25, no. 2, p. 87-96.en
dc.identifier.issn1213-6972 (print)
dc.identifier.issn1213-6980 (CD-ROM)
dc.identifier.issn1213-6964 (on-line)
dc.identifier.uriwscg.zcu.cz/WSCG2017/!_2017_Journal_WSCG-No-2.pdf
dc.identifier.urihttp://hdl.handle.net/11025/26286
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.rights.accessopenAccessen
dc.subjectdetekce mikrovýrazucs
dc.subjectintegrální projekcecs
dc.subjectchi-kvadrátová vzdálenostcs
dc.subject.translatedmicro-expression detectionen
dc.subject.translatedintegral projectionen
dc.subject.translatedchi-squared distanceen
dc.titleMicro-expression detection using integral projectionsen
dc.typečlánekcs
dc.typearticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

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Volume 25, Number 2 (2017)