3D face recognition: A comprehensive survey in 2022
In the past ten years, research on face recognition has shifted to using 3D facial surfaces, as
3D geometric information provides more discriminative features. This comprehensive survey …
3D geometric information provides more discriminative features. This comprehensive survey …
A survey of local feature methods for 3D face recognition
One of the main modules in a face recognition system is feature extraction, which has a
significant effect on the whole system performance. In the past decades, various types of …
significant effect on the whole system performance. In the past decades, various types of …
A face recognition taxonomy and review framework towards dimensionality, modality and feature quality
I Pattnaik, A Dev, AK Mohapatra - Engineering Applications of Artificial …, 2023 - Elsevier
This paper presents a comprehensive review of Automatic Facial Recognition Systems
using integrative and systematic mapping approach. The review is grounded on criteria …
using integrative and systematic mapping approach. The review is grounded on criteria …
Meta-learning-based adversarial training for deep 3D face recognition on point clouds
Recently, deep face recognition using 2D face images has made great advances mainly due
to the readily available large-scale face data. However, deep face recognition using 3D face …
to the readily available large-scale face data. However, deep face recognition using 3D face …
A kinect-based wearable face recognition system to aid visually impaired users
LB Neto, F Grijalva, VRML Maike… - … on Human-Machine …, 2016 - ieeexplore.ieee.org
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 …
at aiding the blind and low-vision people. The system uses a Microsoft Kinect sensor as a …
A two-phase weighted collaborative representation for 3D partial face recognition with single sample
Abstract 3D face recognition with the availability of only partial data (missing parts,
occlusions and data corruptions) and single training sample is a highly challenging task …
occlusions and data corruptions) and single training sample is a highly challenging task …
A fast and robust 3D face recognition approach based on deeply learned face representation
With the superiority of three-dimensional (3D) scanning data, eg, illumination invariance and
pose robustness, 3D face recognition theoretically has the potential to achieve better results …
pose robustness, 3D face recognition theoretically has the potential to achieve better results …
Learning directly from synthetic point clouds for “in-the-wild” 3D face recognition
Point clouds-based networks have achieved great attention in 3D object classification,
segmentation, and indoor scene semantic parsing, but its application to 3D face recognition …
segmentation, and indoor scene semantic parsing, but its application to 3D face recognition …
Adaptive feature selection-based AdaBoost-KNN with direct optimization for dynamic emotion recognition in human–robot interaction
L Chen, M Li, W Su, M Wu, K Hirota… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
AdaBoost-KNN using adaptive feature selection with direct optimization is proposed for
dynamic emotion recognition in human-robot interaction, where the real-time dynamic …
dynamic emotion recognition in human-robot interaction, where the real-time dynamic …
A novel descriptor (LGBQ) based on Gabor filters
Recently, many existing automatic facial verification methods have focused on learning the
optimal distance measurements between facials. Especially in the case of learning facial …
optimal distance measurements between facials. Especially in the case of learning facial …