Multi-feature-based robust face detection and coarse alignment method via multiple kernel learning

Bo Sun; Di Zhang; Jun He; Lejun Yu; Xuewen Wu

doi:10.1117/12.2194254

21 October 2015 Multi-feature-based robust face detection and coarse alignment method via multiple kernel learning

Bo Sun, Di Zhang, Jun He, Lejun Yu, Xuewen Wu

Proceedings Volume 9652, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence XI; and Optical Materials and Biomaterials in Security and Defence Systems Technology XII; 96520H (2015) https://doi.org/10.1117/12.2194254
Event: SPIE Security + Defence, 2015, Toulouse, France

Abstract

Face detection and alignment are two crucial tasks to face recognition which is a hot topic in the field of defense and security, whatever for the safety of social public, personal property as well as information and communication security. Common approaches toward the treatment of these tasks in recent years are often of three types: template matching-based, knowledge-based and machine learning-based, which are always separate-step, high computation cost or fragile robust. After deep analysis on a great deal of Chinese face images without hats, we propose a novel face detection and coarse alignment method, which is inspired by those three types of methods. It is multi-feature fusion with Simple Multiple Kernel Learning¹ (Simple-MKL) algorithm. The proposed method is contrasted with competitive and related algorithms, and demonstrated to achieve promising results.

Citation Download Citation

Bo Sun, Di Zhang, Jun He, Lejun Yu, and Xuewen Wu "Multi-feature-based robust face detection and coarse alignment method via multiple kernel learning", Proc. SPIE 9652, Optics and Photonics for Counterterrorism, Crime Fighting, and Defence XI; and Optical Materials and Biomaterials in Security and Defence Systems Technology XII, 96520H (21 October 2015); https://doi.org/10.1117/12.2194254

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