dc.contributor.author | Lindi, Gieril Ánde | |
dc.date.accessioned | 2016-10-10T13:37:23Z | |
dc.date.available | 2016-10-10T13:37:23Z | |
dc.date.issued | 2016-06-15 | |
dc.identifier.uri | http://hdl.handle.net/11250/2414009 | |
dc.description | Master's thesis in Cybernetics and signal processing | nb_NO |
dc.description.abstract | The main objective of this thesis was to implement a demonstration behaviour for the
NAO robot, with focus on face recognition. To achieve this, a complete framework for face
recognition that is capable of real-time processing and learning had to be implemented.
A pre-trained database is not needed, as the framework learns new faces on-the-fly.
For real time processing and recognition the computation lightness is important, as well as
the precision. Therefore the LBP descriptor was chosen to be the main descriptor in the
mentioned framework. The K- Nearest Neighbour classifier is used for matching, where
the distance metric between the face representations is calculated using the χ2 distance
score.
To be able to classify an unknown face, a threshold is used when predicting. If the χ2
distance score returned is above a set threshold the learning module is initialized, where
only key frames are extracted from the face and stored in the database. These key frames
represent the face in different poses and expressions, thus assuring robustness for the
real-time face recognition system.
The NAO robot acts upon various ”events” based on the classifications done by the
system.
The performance of the system is evaluated by using available pre-existing face databases
consisting of faces under varying conditions regarding illumination, facial expressions and
pose. These tests were done by performing a K-fold cross validations. The validation
results show high performance for both precision and speed. The face recognition system
achieves 91.7% precision when evaluated on the yale face database A, and 99.8% precision
for the AT&T database. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | University of Stavanger, Norway | nb_NO |
dc.relation.ispartofseries | Masteroppgave/UIS-TN-IDE/2016; | |
dc.subject | informasjonsteknologi | nb_NO |
dc.subject | kybernetikk | nb_NO |
dc.subject | automatisering | nb_NO |
dc.subject | signalbehandling | nb_NO |
dc.subject | ansiktsgjenkjenningssystem | nb_NO |
dc.title | Utvikling av ansiktsgjenkjenningssystem for bruk på NAO robot | nb_NO |
dc.title.alternative | Development of face recognition system for use on the NAO robot | nb_NO |
dc.type | Master thesis | nb_NO |
dc.subject.nsi | VDP::Technology: 500::Information and communication technology: 550::Technical cybernetics: 553 | nb_NO |