Title | ||
---|---|---|
Projection Metric Learning on Grassmann Manifold with Application to Video based Face Recognition |
Abstract | ||
---|---|---|
In video based face recognition, great success has been made by representing videos as linear subspaces, which typically lie in a special type of non-Euclidean space known as Grassmann manifold. To leverage the kernel-based methods developed for Euclidean space, several recent methods have been proposed to embed the Grassmann manifold into a high dimensional Hilbert space by exploiting the well established Project Metric, which can approximate the Riemannian geometry of Grassmann manifold. Nevertheless, they inevitably introduce the drawbacks from traditional kernel-based methods such as implicit map and high computational cost to the Grassmann manifold. To overcome such limitations, we propose a novel method to learn the Projection Metric directly on Grassmann manifold rather than in Hilbert space. From the perspective of manifold learning, our method can be regarded as performing a geometry-aware dimensionality reduction from the original Grassmann manifold to a lower-dimensional, more discriminative Grassmann manifold where more favorable classification can be achieved. Experiments on several real-world video face datasets demonstrate that the proposed method yields competitive performance compared with the state-of-the-art algorithms. |
Year | DOI | Venue |
---|---|---|
2015 | 10.1109/CVPR.2015.7298609 | 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) |
Keywords | Field | DocType |
projection metric learning,video based face recognition,videos representation,linear subspaces,nonEuclidean space,Grassmann manifold,kernel-based methods,high dimensional Hilbert space,Riemannian geometry,implicit map,manifold learning,geometry-aware dimensionality reduction | Computer science,Manifold alignment,Hilbert manifold,Artificial intelligence,Nonlinear dimensionality reduction,Statistical manifold,Pseudo-Riemannian manifold,Topology,Information geometry,Fisher information metric,Pattern recognition,Algebra,Euclidean space | Conference |
Volume | Issue | ISSN |
2015 | 1 | 1063-6919 |
Citations | PageRank | References |
5 | 0.39 | 33 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Zhiwu Huang | 1 | 252 | 15.26 |
Ruiping Wang | 2 | 894 | 41.60 |
Shiguang Shan | 3 | 6322 | 283.75 |
Xilin Chen | 4 | 6291 | 306.27 |