Facial features location by analytic boosted cascade detector

Authors:
Lei Wang;Beiji Zou;Jiaguang Sun
Affiliations:
School of Computer and Communication, Hunan University, China;School of Information Science and Engineering, Central South University, China;School of Software, Tsinghua University, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
Year:
2005

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Abstract

We describe a novel technique called Analytic Boosted Cascade Detector (ABCD) to automatically locate features on the human face. ABCD extends the original Boosted Cascade Detector (BCD) in three ways: (i) a probabilistic model is included to connect the classifier responses with the facial features; (ii) a features location method based on the probabilistic model is formulated; (iii) a selection criterion for face candidates is presented. The new technique melts face detection and facial features location into a unified process. It outperforms Average Positions (AVG) and Boosted Classifiers + best response (BestHit). It also shows great speed superior to the methods based on nonlinear optimization, e.g. AAM and SOS.