A Supervised Face Recognition in Still Images using Interest Points
Guilherme Felippe Plichoski, Guilherme Metzger, Chidambaram Chidambaram · Anais do Computer on the Beach · 2018
In recent decades, face recognition (FR) has been studied due to technological advances and increased computational power of equipments. This happens also by the emergence of concern with security issues, and the possibility of its application in various domains. In this context, this study was developed in order to present an approach for recognition of individuals through facial images. For this, we used interest points detectors called SIFT (Scale Invariant Feature Transform) and SURF (Speeded up Robust Features), which are invariant to certain complicating factors found in the recognition process, such as lighting changes, scale and rotation. Using the face images of 138 individuals, the results obtained from the experiments show that the approach is suitable for face recognition.