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3D-ansiktsigenkänning med Kinect: En studie i ansiktsigenkänning med Kinect och dess beroende påansiktets horisontella rotation
KTH, School of Computer Science and Communication (CSC).
KTH, School of Computer Science and Communication (CSC).
2014 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [sv]

Denna rapport syftar till att utforska och visa på möjligheten till ansiktsigenkänning vilket görs lättillgängligt för allmänheten genom Microsoft Kinect for XBOX360 och eventuella framtida liknande lösningar med lågupplösta 3D-sensorer. Det finns många komplicerande faktorer inom ansiktsigenkänning och däribland ansiktsrotation. Beroendet på ansiktets horisontella vinklar i förhållande till Kinectenheten undersöks för 5 testsubjekt genom användandet av en 3D-baserad matchningsalgoritm.Detta sker med en metod baserad på Microsoft Kinect Face Tracking SDK och de ansiktsmodeller i 3D denna levererar. Undersökningens resultat är i linje med ansiktsigenkänningens problematik. Ett bättre resultat fås för sant positiva matchningar mellan frontala subjekt jämfört med horisontellt roterade ansikten. Undersökningen visar dock på att ansiktsigenkänning inte är helt underpresterande för de senare och att Kinect och Face Trackings SDK, utan större ingrepp, hanterar ansiktsigenkänning ganska bra.

Abstract [en]

This report aims to explore and show the possibilities of face recognition, which are made available to the public through Microsoft Kinect for XBOX 360 and future similar solutions with low resolution 3D sensors. There are many complicating factors in face recognition such as the rotation of the subjects face. The dependency of the face rotation in relation to the Kinect sensor is studied for 5 test subjects by using a 3D based matching algorithm. This is done with the Microsoft Kinect Face Tracking SDK and the 3D face models this SDK provides. The result of the study is in line with the complications with head rotation in facial recognition. For true positive matches frontal subjects gain better results compared with horizontally rotated subject faces. The study shows that the latter are not completely underperforming the frontal matches however, and that Kinect and Face Tracking SDK, without great interventions, handle face recognition rather well.

Place, publisher, year, edition, pages
2014.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-157682OAI: oai:DiVA.org:kth-157682DiVA: diva2:771062
Examiners
Available from: 2014-12-12 Created: 2014-12-12 Last updated: 2014-12-12Bibliographically approved

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Type fulltextMimetype application/pdf

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