Adaptation of SIFT Features for Robust Face Recognition

Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The original SIFT algorithm has been successfully applied in general object detection and recognition tasks, panorama stitching and others. One of its more recent uses also includes face recognition, where it was shown to deliver encouraging results. SIFTbased face recognition techniques found in the literature rely heavily on the so-called keypoint detector, which locates interest points in the given image that are ultimately used to compute the SIFT descriptors. While these descriptors are known to be among others (partially) invariant to illumination changes, the keypoint detector is not. Since varying illumination is one of the main issues affecting the performance of face recognition systems, the keypoint detector represents the main source of errors in face recognition systems relying on SIFT features. To overcom...

• Type: Conference
• Year: 2010
• Where: ICIAR
• Authors: Janez Krizaj, Vitomir Struc, Nikola Pavesic
• Keywords: Face Recognition, ICIAR 2010, Image Analysis, Keypoint Detector, Sift Descriptor