A comparative study on face detection and tracking algorithms

被引:24
|
作者
Belaroussi, Rachid [1 ]
Milgram, Maurice [2 ]
机构
[1] LIVIC, IM, IFSITAR, F-78000 Versailles, France
[2] Univ Paris 06, ISIR, UMR 7222, F-75005 Paris, France
关键词
Face detection; OpenCV; Skin color model; Coupled Camshift; COLOR; SEGMENTATION;
D O I
10.1016/j.eswa.2012.01.076
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Face localization is the first stage in many vision based applications and in human-computer interaction. The problem is to define the face location of a person in a color image. The four boosted classifiers embbeded in OpenCV, based on Haar-like features, are compared in terms of speed and efficiency. Skin color distribution is estimated using a non parametric approach. To avoid drifting in color estimate, this model is not updated during the sequence but renewed whenever the face is detected again, that gives the ability to our system to cope with different lighting conditions in a more robust way. Skin color model is then used to localize the face represented by an ellipse: connected component segmentation and a statistical approach, namely the coupled Camshift of Bradsky, are compared in terms of efficiency and speed. The pursuit algorithms are tested on various video sequences, corresponding to various scenarios in terms of illumination, face pose, face size and background complexity (distractor effects). (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:7158 / 7164
页数:7
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