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首页> 外文期刊>International Journal of Engineering Research and Applications >Robust Facial Marks Detection Method Using AAM And SURF
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Robust Facial Marks Detection Method Using AAM And SURF

机译:基于AAM和SURF的鲁棒面部标记检测方法

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In face recognition technology, facial marks identification method is one of the unique facial identification tasks using soft biometrics. Also facial marks information can enhance the face matching score to improve the face recognition performance. As numbers of folk apply their face with cosmetic items, some of the facial marks are invisible or hidden from their faces. In the literature, they used AAM (Active Appearance Model) and LoG (Laplacian of Gaussian) method to detect the facial marks. However, to the best of our knowledge, the methods related to the detection of facial marks are poor in performance in cosmetic applied faces. In this paper, we propose robust method to detect the facial marks such as tattoos, scars, freckles and moles etc. Initially we apply active appearance model (AAM) for facial feature detection purpose. In addition to this prior model we apply Canny edge detector method to detect the facial mark edges. Finally SURF is used to detect the hidden facial marks which are covered by cosmetic items. Hence we argue that the choice of this method gives high accuracy in facial marks detection of the cosmetic applied faces. In fact the use of robust marks detection method with soft biometrics traits performed the best facial recognition technology
机译:在面部识别技术中,面部标记识别方法是使用软生物识别技术的独特面部识别任务之一。面部标记信息还可以增强面部匹配分数以改善面部识别性能。随着许多人用化妆品涂抹他们的脸部,一些面部标记从他们的脸部变得不可见或隐藏。在文献中,他们使用AAM(主动外观模型)和LoG(高斯拉普拉斯)方法来检测面部痕迹。然而,据我们所知,与面部痕迹检测相关的方法在化妆品应用的面部中的性能较差。在本文中,我们提出了一种鲁棒的方法来检测纹身,疤痕,雀斑和痣等面部标记。最初,我们将主动外观模型(AAM)用于面部特征检测。除此现有模型外,我们还使用Canny边缘检测器方法检测面部标记边缘。最后,SURF用于检测被化妆品覆盖的隐藏面部标记。因此,我们认为该方法的选择在化妆品施加的面部的面部标记检测中具有较高的准确性。实际上,使用具有软生物特征的鲁棒性标记检测方法可实现最佳的面部识别技术

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