TY  - CONF
AU  - Fadi Dornaika
AU  - Alireza Bosaghzadeh
AU  - Bogdan Raducanu
A2  - HBU
PY  - 2013//
TI  - Efficient Graph Construction for Label Propagation based Multi-observation Face Recognition
BT  - Human Behavior Understanding 4th International Workshop
SP  - 124
EP  - 135
VL  - 8212
PB  - Springer International Publishing
N2  - Workshop on Human Behavior UnderstandingHuman-machine interaction is a hot topic nowadays in the communities of multimedia and computer vision. In this context, face recognition algorithms (used as primary cue for a person’s identity assessment) work well under controlled conditions but degrade significantly when tested in real-world environments. Recently, graph-based label propagation for multi-observation face recognition was proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot adapt optimally to the data. In this paper, we propose a novel approach for efficient and adaptive graph construction that can be used for multi-observation face recognition as well as for other recognition problems. Experimental results performed on Honda video face database, show a distinct advantage of the proposed method over the standard graph construction methods.
SN  - 0302-9743
SN  - 978-3-319-02713-5
L1  - http://refbase.cvc.uab.es/files/DBR2013.pdf
UR  - http://dx.doi.org/10.1007/978-3-319-02714-2_11
N1  - OR;MV
ID  - Fadi Dornaika2013
ER  -