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

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2527954