Title :
Sketch-based face alignment for thermal face recognition
Author :
Lin Sun ; Dai, X.X.
Author_Institution :
Dept. of Comput. Sci., Zhejiang Univ. City Coll., Hangzhou, China
Abstract :
In this paper, we present a novel face alignment approach in thermal infrared face recognition. The alignment procedure is based on closest point set matching between sketch faces. Linear combination of positional and local pattern features is embedded in the pointwise distance to solve the local minimum problem for ICP due to edge noise in sketch faces. The comprehensive experiments, including intra-class, inter-class and variable expressions, show the alignment accuracy and face recognition performance results of our algorithm compared to manual labelling, ICP and congealing methods.
Keywords :
emotion recognition; face recognition; feature extraction; image matching; infrared imaging; set theory; ICP; closest point set matching; interclass expressions; intraclass expressions; local minimum problem; local pattern features; pointwise distance; positional pattern features; sketch-based face alignment; thermal infrared face recognition; variable expressions; Face; Face recognition; Histograms; Image edge detection; Iterative closest point algorithm; Labeling; Manuals;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4