Recent statistics of the World Health Organization (WHO), published in October 2017,
estimate that more than 253 million people worldwide suffer from visual impairment (VI) with …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

In the last decade, advances and popularity of low-cost RGB-D sensors have enabled us to
acquire depth information of objects. Consequently, researchers began to solve face …

Aspired to build intelligent agents that can assist humans in daily life, researchers and
engineers, both from academia and industry, have kept advancing the state-of-the-art in …

In this paper, we introduce a real-time face recognition (and announcement) system targeted
at aiding the blind and low-vision people. The system uses a Microsoft Kinect sensor as a …

In order to improve the accuracy and speed of three-dimensional face recognition, this paper
proposes a three-dimensional face recognition method combining LBP and SVM. First, the …

Near-infrared (NIR) face recognition has attracted increasing attention because of its
advantage of illumination invariance. However, traditional face recognition methods based …

Face recognition algorithms generally utilize 2D images for feature extraction and matching.
To achieve higher resilience toward covariates, such as expression, illumination, and pose …

As face recognition progresses from constrained scenarios to unconstrained scenarios, new
challenges such as large pose, bad illumination, and partial occlusion, are encountered …

With the increasing availability of consumer depth sensors, 3D face recognition (FR) has
attracted more and more attention. However, the data acquired by these sensors are often …