Title :
Summation Invariant Features for 3D Face Recognition
Author :
Lin, Wei-Yang ; Boston, Nigel ; Hu, Yu Hen
Author_Institution :
Dept. of Electr. & Comput. Eng., Wisconsin-Madison Univ., Madison, WI
fDate :
Oct. 30 2005-Nov. 2 2005
Abstract :
A novel summation invariant feature under transformation group action for 3D surface recognition is proposed, and its application to 3D face recognition is investigated. Based on a systematic mathematical procedure called moving frame, we derived the summation invariant feature that is invariant under affine transformation. Compared with classical differential invariants, such as the mean curvature or the Gaussian curvature, summation invariant feature is far less sensitive to observation noise in the data. A further enhancement leads to a new type of invariant 3D surface shape descriptor called a semi-local summation invariant. We demonstrate one important, potential application of this new feature to 3D human face recognition
Keywords :
affine transforms; face recognition; 3D face recognition; affine transformation; invariant feature summation; moving frame; Application software; Computer vision; Data acquisition; Face recognition; Gaussian noise; Humans; Integral equations; Noise shaping; Shape; Signal to noise ratio;
Conference_Titel :
Multimedia Signal Processing, 2005 IEEE 7th Workshop on
Conference_Location :
Shanghai
Print_ISBN :
0-7803-9288-4
Electronic_ISBN :
0-7803-9289-2
DOI :
10.1109/MMSP.2005.248621