کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6940389 | 1450012 | 2018 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fast and robust occluded face detection in ATM surveillance
ترجمه فارسی عنوان
تشخیص چهره سریع و قوی در نظارت از دستگاه خودپرداز
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Crimes with respect to ATMs (Automatic Teller Machines) have attracted more and more attention, where criminals deliberately cover their faces in order to avoid being identified. This paper proposes a fast and robust face occlusion detection algorithm for ATM surveillance, which is demonstrated to be effective and efficient to handle arbitrarily occluded faces. In this algorithm, we innovatively propose to make use of the Omega shape formed by the head and shoulder of the person for head localization to tackle severe face occlusion. For this purpose, we first construct a novel energy function for elliptical head contour detection. Then, we develop a fast and robust head tracking algorithm, which utilizes the gradient and shape cues in a Bayesian framework. Lastly, to verify whether a detected head is occluded or not, we propose to fuse information from both skin color and face structure using the AdaBoost algorithm. Experimental results on real world data show that our proposed algorithm can achieve 98.64% accuracy on face detection and 98.56% accuracy on face occlusion detection, even though there are severe occlusions in faces, at a speed of up to 12 frames per second.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 107, 1 May 2018, Pages 33-40
Journal: Pattern Recognition Letters - Volume 107, 1 May 2018, Pages 33-40
نویسندگان
Tao Zhang, Jingjing Li, Wenjing Jia, Jun Sun, Huihua Yang,