کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4969248 | 1449927 | 2017 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Robust face anti-spoofing with depth information
ترجمه فارسی عنوان
چهره قوی با اطلاعات عمیق ضد خرابکارانه
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کلمات کلیدی
ضد حشره کش چهره، اطلاعات عمق، شبکه عصبی متقاطع،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
With the prevalence of face authentication applications, the prevention of malicious attack from fake faces such as photos or videos, i.e., face anti-spoofing, has attracted much attention recently. However, while an increasing number of works on the face anti-spoofing have been reported based on 2D RGB cameras, most of them cannot handle various attacking methods. In this paper we propose a robust representation jointly modeling 2D textual information and depth information for face anti-spoofing. The textual feature is learned from 2D facial image regions using a convolutional neural network (CNN), and the depth representation is extracted from images captured by a Kinect. A face in front of the camera is classified as live if it is categorized as live using both cues. We collected a face anti-spoofing experimental dataset with depth information, and reported extensive experimental results to validate the robustness of the proposed method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 49, November 2017, Pages 332-337
Journal: Journal of Visual Communication and Image Representation - Volume 49, November 2017, Pages 332-337
نویسندگان
Yan Wang, Fudong Nian, Teng Li, Zhijun Meng, Kongqiao Wang,