Multimedia Technology IV – Farag, Yang & Jiao (Eds)
© 2015 Taylor & Francis Group, London, ISBN: 978-1-138-02794-7
Sparse representation and random forests based face recognition
with single sample per person
Tao Xu, Hongwei Hu, Qiaofeng Ma & Bo Ma
Beijing Laboratory of Intelligent Information Technology, School of Computer Science and Technology,
Beijing Institute of Technology, Beijing, China
ABSTRACT: Traditional face recognition methods usually require a large number of training samples. In
some specific applications, however, we can only obtain one facial image as training sample for each person,
which is usually referred to as single sample per person face recognition. The recognition rates will decrease
dramatically using traditional methods ...