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 …
3d face recognition: Two decades of progress and prospects
Three-dimensional (3D) face recognition has been extensively investigated in the last two
decades due to its wide range of applications in many areas, such as security and forensics …
decades due to its wide range of applications in many areas, such as security and forensics …
Thingi10k: A dataset of 10,000 3d-printing models
Q Zhou, A Jacobson - arXiv preprint arXiv:1605.04797, 2016 - arxiv.org
Empirically validating new 3D-printing related algorithms and implementations requires
testing data representative of inputs encountered\emph {in the wild}. An ideal benchmarking …
testing data representative of inputs encountered\emph {in the wild}. An ideal benchmarking …
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 …
Towards 3D face recognition in the real: a registration-free approach using fine-grained matching of 3D keypoint descriptors
Registration algorithms performed on point clouds or range images of face scans have been
successfully used for automatic 3D face recognition under expression variations, but have …
successfully used for automatic 3D face recognition under expression variations, but have …
meshSIFT: Local surface features for 3D face recognition under expression variations and partial data
D Smeets, J Keustermans, D Vandermeulen… - Computer Vision and …, 2013 - Elsevier
Matching 3D faces for recognition is a challenging task caused by the presence of
expression variations, missing data, and outliers. In this paper the meshSIFT algorithm and …
expression variations, missing data, and outliers. In this paper the meshSIFT algorithm and …
3-D face recognition: features, databases, algorithms and challenges
Face recognition is being widely accepted as a biometric technique because of its non-
intrusive nature. Despite extensive research on 2-D face recognition, it suffers from poor …
intrusive nature. Despite extensive research on 2-D face recognition, it suffers from poor …
[HTML][HTML] Matching 3D face scans using interest points and local histogram descriptors
In this work, we propose and experiment an original solution to 3D face recognition that
supports face matching also in the case of probe scans with missing parts. In the proposed …
supports face matching also in the case of probe scans with missing parts. In the proposed …
Learning the spherical harmonic features for 3-D face recognition
In this paper, a competitive method for 3-D face recognition (FR) using spherical harmonic
features (SHF) is proposed. With this solution, 3-D face models are characterized by the …
features (SHF) is proposed. With this solution, 3-D face models are characterized by the …
3D face recognition: A survey
Face recognition is one of the most studied research topics in the community. In recent
years, the research on face recognition has shifted to using 3D facial surfaces, as more …
years, the research on face recognition has shifted to using 3D facial surfaces, as more …