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Article

Real-Time Pre-Identification and Cascaded Detection for Tiny Faces

by 1,†, 1,†, 2,3,* and 1
1
School of Information Engineering, Nanchang University, Nanchang 330031, China
2
School of Software, Nanchang University, Nanchang 330047, China
3
Jiangxi Key Laboratory of Smart City, Nanchang 330047, China
*
Author to whom correspondence should be addressed.
The first two authors contributed equally to this work.
Appl. Sci. 2019, 9(20), 4344; https://doi.org/10.3390/app9204344
Received: 6 September 2019 / Revised: 26 September 2019 / Accepted: 6 October 2019 / Published: 15 October 2019
(This article belongs to the Special Issue Advanced Biometrics with Deep Learning)
Although the face detection problem has been studied for decades, searching tiny faces in the whole image is still a challenging task, especially in low-resolution images. Traditional face detection methods are based on hand-crafted features, but the features of tiny faces are different from those of normal-sized faces, and thus the detection robustness cannot be guaranteed. In order to alleviate the problem in existing methods, we propose a pre-identification mechanism and a cascaded detector (PMCD) for tiny-face detection. This pre-identification mechanism can greatly reduce background and other irrelevant information. The cascade detector is designed with two stages of deep convolutional neural network (CNN) to detect tiny faces in a coarse-to-fine manner, i.e., the face-area candidates are pre-identified as region of interest (RoI) based on a real-time pedestrian detector and the pre-identification mechanism, the set of RoI candidates is the input of the second sub-network instead of the whole image. Benefiting from the above mechanism, the second sub-network is designed as a shallow network which can keep high accuracy and real-time performance. The accuracy of PMCD is at least 4% higher than the other state-of-the-art methods on detecting tiny faces, while keeping real-time performance. View Full-Text
Keywords: face detection; tiny faces; pre-identification mechanism; cascaded detector; deep learning; convolutional neural network face detection; tiny faces; pre-identification mechanism; cascaded detector; deep learning; convolutional neural network
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MDPI and ACS Style

Yang, Z.; Li, J.; Min, W.; Wang, Q. Real-Time Pre-Identification and Cascaded Detection for Tiny Faces. Appl. Sci. 2019, 9, 4344. https://doi.org/10.3390/app9204344

AMA Style

Yang Z, Li J, Min W, Wang Q. Real-Time Pre-Identification and Cascaded Detection for Tiny Faces. Applied Sciences. 2019; 9(20):4344. https://doi.org/10.3390/app9204344

Chicago/Turabian Style

Yang, Ziyuan, Jing Li, Weidong Min, and Qi Wang. 2019. "Real-Time Pre-Identification and Cascaded Detection for Tiny Faces" Applied Sciences 9, no. 20: 4344. https://doi.org/10.3390/app9204344

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