Multi-view face identification and pose estimation using B-spline interpolation
Document Type
Article
Publication Date
2-1-2005
Abstract
The available face views in the training set are mostly limited. In this paper, we present a view interpolation method using nonlinear B-spline on face manifolds. Two models, the inner-outer ellipse model and the moment of inertia model, are developed to estimate the pose orientation. We use the limited view-pose face images to form the pose eigen space. Then, based on these nonlinear manifolds we form a B-spline for each individual. Identification is to compute the shortest Euclidean distance from a given test view to the nearest point within one of these B-splines. Once the test view is classified as a familiar individual in the training set, not only can the individual be identified, but also the pose angle can be estimated. Experimental results show that B-spline interpolation can achieve a recognition rate of 95%. © 2004 Elsevier Inc. All rights reserved.
Identifier
11344286621 (Scopus)
Publication Title
Information Sciences
External Full Text Location
https://doi.org/10.1016/j.ins.2004.05.006
ISSN
00200255
First Page
189
Last Page
204
Issue
3-4
Volume
169
Recommended Citation
Shih, Frank; Fu, Camel; and Zhang, Kai, "Multi-view face identification and pose estimation using B-spline interpolation" (2005). Faculty Publications. 19791.
https://digitalcommons.njit.edu/fac_pubs/19791
