Title of article :
SWF-SIFT Approach for Infrared Face Recognition
Author/Authors :
TAN, Chunlin Harbin Institute of Technology - School of Aerospace, China , WANG, Hongqiao Xi an Research Institute of High Technology, China , WANG, Hongqiao Tsinghua University - Department of Computer Science and Technology, China , PEI, Deli Tsinghua University - Department of Computer Science and Technology, China
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 usedin 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.
Keywords :
infrared image , human face recognition , scale invariant feature transform (SIFT) , star , styled window filter (SWF)
Journal title :
Tsinghua Science and Technology
Journal title :
Tsinghua Science and Technology
