@article{TAN2010, 
author = {Chunlin TAN and Hongqiao WANG and Deli PEI},
title = {SWF-SIFT Approach for Infrared Face Recognition},
year = {2010},
journal = {Tsinghua Science and Technology},
volume = {15},
number = {3},
pages = {357-362},
keywords = {infrared image, human face recognition, scale invariant feature transform (SIFT), star-styled window filter (SWF)},
url = {https://www.sciopen.com/article/10.1016/S1007-0214(10)70074-2},
doi = {10.1016/S1007-0214(10)70074-2},
abstract = {The scale invariant feature transform (SIFT) feature descriptor is invariant to image scale and location, and is robust to affine transformations and changes in illumination, so it is a powerful descriptor used in many applications, such as object recognition, video tracking, and gesture recognition. However, in noisy and non-rigid object recognition applications, especially for infrared human face recognition, SIFT-based algorithms may mismatch many feature points. This paper presents a star-styled window filter-SIFT (SWF-SIFT) scheme to improve the infrared human face recognition performance by filtering out incorrect matches. Performance comparisons between the SIFT and SWF-SIFT algorithms show the advantages of the SWF-SIFT algorithm through tests using a typical infrared human face database.}
}