Abstract
In this paper, we propose a new approach to Bayesian subspace method for face recognition. We review this method and point out some weak points in its assumptions and propose a practical solution to overcome those weak points. In addition, we present an efficient way to estimate the high dimensional Gaussian density function.
Original language | English |
---|---|
Title of host publication | Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition IPCV'12 |
Editors | Hamid R Arabnia, Leonidas Deligiannidis |
Place of Publication | USA |
Publisher | CSREA Press |
Pages | 547-553 |
Number of pages | 7 |
Volume | 1 |
ISBN (Print) | 9781601322232, 9781601322259 |
Publication status | Published - 2012 |
Event | 16th International Conference on Image Processing, Computer Vision & Pattern Recognition - Las Vegas, Las Vegas, United States Duration: 16 Jul 2012 → 19 Jul 2012 https://worldacademyofscience.org/worldcomp12/ws/conferences/ipcv12/General%20Information.html |
Conference
Conference | 16th International Conference on Image Processing, Computer Vision & Pattern Recognition |
---|---|
Abbreviated title | IPCV 2012 |
Country/Territory | United States |
City | Las Vegas |
Period | 16/07/12 → 19/07/12 |
Internet address |