Abstract
This paper presents a face recognition algorithm based on the matching of local features extracted from face images, namely SIFT. Some of the earlier approaches based on SIFT matching are sensitive to registration errors and usually rely on a very good initial alignment and illumination of the faces to be recognised. The method is based on a new image matching strategy between face images, that first establishes correspondences between feature points, and then uses the number of correct correspondences, together with the total number of matches and detected features, to determine the likelihood of the similarity between the face images.
The experimental results, performed on different datasets, demonstrate the effectiveness of the proposed algorithm for automatic face identification. More exhaustive experiments are planned in order to perform a fair comparison with other state of the art methods based on local features.
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Di Mella, M., Isgrò, F. (2015). Face Recognition from Robust SIFT Matching. In: Murino, V., Puppo, E. (eds) Image Analysis and Processing — ICIAP 2015. ICIAP 2015. Lecture Notes in Computer Science(), vol 9280. Springer, Cham. https://doi.org/10.1007/978-3-319-23234-8_28
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