Robust Face Recognition on Adverse 3D Data - Attaining Expression & Occlusion Invariance Using Machine Learning
Ladda ner
Typ
Examensarbete för masterexamen
Master Thesis
Master Thesis
Program
Complex adaptive systems (MPCAS), MSc
Publicerad
2013
Författare
Kågebäck, Mikael
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
The emerging field of high resolution mobile and inexpensive depth cameras, promise to revolutionize many parts of computer vision. One area in particular where 3D data has been shown to improve performance, is face recognition. Using a combination of local and global pattern matching and a committee of neural networks, this thesis present a robust 3D face recognition approach, decisively outperforming current methods. The system is evaluated on the Bosphorus database, a challenging benchmarking dataset that include face scans with both facial expressions and partial occlusions, captured in angles of up to 90 rotation. The proposed system achieves a recognition rate of 98:9%, which is the highest recognition rate ever reported on the Bosphorus database, improving the state of the art by 5:2%.
Beskrivning
Ämne/nyckelord
Teknisk fysik , Hållbar utveckling , Informations- och kommunikationsteknik , Transport , Engineering physics , Sustainable Development , Information & Communication Technology , Transport