@inproceedings{294cbaf1495a4f4b89fb9fc644c7f4ab,
title = "Gender classification using the profile",
abstract = "Gender classification has attracted a lot of attention in computer vision and pattern recognition. In this paper, we propose a gender classification method. First, we present a robust profile extraction algorithm; Second, we implement Principal Components Analysis (PCA) and Independent Components Analysis (ICA) to extract discriminative features from profile to estimate the face gender via SVM. Our experimental results on Bosphorus 3D face database show that our proposed method works well.",
keywords = "feature extraction, gender classification, ICA, PCA",
author = "Wankou Yang and Amrutha Sethuram and Eric Patternson and Karl Ricanek and Changyin Sun",
year = "2011",
doi = "10.1007/978-3-642-21090-7\_34",
language = "英语",
isbn = "9783642210891",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 2",
pages = "288--295",
booktitle = "Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011",
edition = "PART 2",
note = "8th International Symposium on Neural Networks, ISNN 2011 ; Conference date: 29-05-2011 Through 01-06-2011",
}