DocumentCode :
2527954
Title :
Multiscale Integral Invariants For Facial Landmark Detection in 2.5D Data
Author :
Slater, Adam ; Hu, Yu Hen ; Boston, Nigel
Author_Institution :
Wisconsin Univ., Madison
fYear :
2007
fDate :
1-3 Oct. 2007
Firstpage :
175
Lastpage :
178
Abstract :
In this paper, we introduce a novel 3D surface landmark detection method using a 3D integral invariant feature extended from that proposed by Manay et al. for 2D contours. We apply this new feature to detect the nose tips of 2.5D range images of human faces. Using the Face Recognition Grand Challenge 2.0 dataset, our method compares favorably with a recently proposed competing method.
Keywords :
face recognition; feature extraction; object detection; 3D integral invariant feature extension; facial landmark detection; human faces; multiscale integral invariants; Computer vision; Data engineering; Face detection; Face recognition; Humans; Image converters; Image storage; Iterative algorithms; Mathematics; Nose;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Signal Processing, 2007. MMSP 2007. IEEE 9th Workshop on
Conference_Location :
Crete
Print_ISBN :
978-1-4244-1274-7
Type :
conf
DOI :
10.1109/MMSP.2007.4412846
Filename :
4412846
Link To Document :
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