@inproceedings{35ce52db6eda48d886ac083b9e3ef82e,
title = "3D face analysis for distinct features using statistical randomization",
abstract = "It is a fascinating yet challenging problem to accurately and efficiently localize regionally distinct features between face groups in multi-dimensional signal processing and analysis. Given a data with unknown distribution and small sample size, we propose a new statistical analysis framework using hybrid randomization (i.e., permutation) tests to improve the system's efficiency in identifying distinct features. The proposed method fits the nonparametric distribution of the test statistic with Pearson distribution series. We bypass the tedious online randomization via calculating the first four moments of the permutation distribution. This can reduce the computational complexity from O(n!) to O(n2) over traditional methods for the modified Hotelling's T2 test statistics. Experiments on simulated data and 3D face analysis demonstrate the efficiency, accuracy and robustness of the proposed approach.",
keywords = "3D face analysis, Feature selection, Randomization test",
author = "Chunxiao Zhou and Yuxiao Hu and Yun Fu and Huixia Wang and Huang, {Thomas S.} and Wang, {Yongmei Michelle}",
year = "2008",
doi = "10.1109/ICASSP.2008.4517776",
language = "English (US)",
isbn = "1424414849",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "981--984",
booktitle = "2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP",
note = "2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP ; Conference date: 31-03-2008 Through 04-04-2008",
}