| Author(s): |
P J. Phillips; Jingjing Zheng; Ming-Yu Liu; Rama Chellappa; |
| Title: |
A Grassmann Manifold-based Domain Adaptation Approach |
| Published: |
November 20, 2012 |
| Abstract: |
Domain adaptation algorithms that handle shifts in the distribution between training and testing data are receiving much attention in computer vision. Recently, a Grassmann manifold-based domain adaptation algorithm that models the domain shift using intermediate subspaces along the geodesic connecting the source and target domains was presented in [6]. We build upon this work and propose replacing the step of concatenating feature projections on a very few sampled inter- mediate subspaces by directly integrating the distance between feature projections along the geodesic. The proposed approach considers all the intermediate sub- spaces along the geodesic. Thus, it is a more principled way of quantifying the cross-domain distance. We present the results of experiments on two standard datasets and show that the proposed algorithm yields favorable performance over previous approaches. |
| Conference: |
International Conference on Pattern Recognition |
| Proceedings: |
Proceedings of the International Conference on Pattern Recognition |
| Location: |
Tuskuba Science City, -1 |
| Dates: |
November 11-15, 2012 |
| Keywords: |
biometrics; |
| Research Areas: |
Biometrics |
| PDF version: |
 Click here to retrieve PDF version of paper (1MB) |
