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
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;
Conference_Titel :
Multimedia Signal Processing, 2007. MMSP 2007. IEEE 9th Workshop on
Conference_Location :
Crete
Print_ISBN :
978-1-4244-1274-7
DOI :
10.1109/MMSP.2007.4412846