Demographic-Assisted Age-Invariant Face Recognition and Retrieval
AbstractDemographic estimation of human face images involves estimation of age group, gender, and race, which finds many applications, such as access control, forensics, and surveillance. Demographic estimation can help in designing such algorithms which lead to better understanding of the facial aging process and face recognition. Such a study has two parts—demographic estimation and subsequent face recognition and retrieval. In this paper, first we extract facial-asymmetry-based demographic informative features to estimate the age group, gender, and race of a given face image. The demographic features are then used to recognize and retrieve face images. Comparison of the demographic estimates from a state-of-the-art algorithm and the proposed approach is also presented. Experimental results on two longitudinal face datasets, the MORPH II and FERET, show that the proposed approach can compete the existing methods to recognize face images across aging variations. View Full-Text
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Sajid, M.; Shafique, T.; Manzoor, S.; Iqbal, F.; Talal, H.; Samad Qureshi, U.; Riaz, I. Demographic-Assisted Age-Invariant Face Recognition and Retrieval. Symmetry 2018, 10, 148.
Sajid M, Shafique T, Manzoor S, Iqbal F, Talal H, Samad Qureshi U, Riaz I. Demographic-Assisted Age-Invariant Face Recognition and Retrieval. Symmetry. 2018; 10(5):148.Chicago/Turabian Style
Sajid, Muhammad; Shafique, Tamoor; Manzoor, Sohaib; Iqbal, Faisal; Talal, Hassan; Samad Qureshi, Usama; Riaz, Imran. 2018. "Demographic-Assisted Age-Invariant Face Recognition and Retrieval." Symmetry 10, no. 5: 148.
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