Journal ArticleDOI
Robust regional bounding spherical descriptor for 3D face recognition and emotion analysis
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TLDR
A robust regional bounding spherical descriptor (RBSR) is proposed to facilitate 3D face recognition and emotion analysis and three largest available databases, FRGC v2, CASIA and BU-3DFE, are contributed to the performance comparison.About:
This article is published in Image and Vision Computing.The article was published on 2015-03-01. It has received 42 citations till now. The article focuses on the topics: Facial recognition system.read more
Citations
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Journal ArticleDOI
A survey of local feature methods for 3D face recognition
TL;DR: This survey presents a state-of-the-art for 3D face recognition using local features, with the main focus being the extraction of these features.
Journal ArticleDOI
3D face recognition: a survey
Song Zhou,Sheng Xiao +1 more
TL;DR: The history and the most recent progresses in 3D face recognition research domain are summarized, and the frontier research results are introduced in three categories: pose-invariant recognition, expression- Invariant Recognition, and occlusion-invarant recognition.
Journal ArticleDOI
A survey of emotion recognition methods with emphasis on E-Learning environments
Maryam Imani,Gholam Ali Montazer +1 more
TL;DR: According to the findings of this research, the multi-modal emotion recognition systems through information fusion as facial expressions, body gestures and user's messages provide better efficiency than the single- modal ones.
Journal ArticleDOI
3-D face recognition: features, databases, algorithms and challenges
TL;DR: An extensive survey of recent 3-D face recognition techniques in terms of feature detection, classifiers as well as published algorithms that address expression and occlusion variation challenges is presented followed by critical comments on the published work.
Journal ArticleDOI
Near infrared face recognition using Zernike moments and Hermite kernels
TL;DR: Experimental results on CASIA NIR and PolyU NIR face databases clearly show that the proposed face recognition method achieves significantly higher face recognition accuracy compared with existing methods.
References
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Journal ArticleDOI
Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
TL;DR: In this article, the maximal statistical dependency criterion based on mutual information (mRMR) was proposed to select good features according to the maximal dependency condition. But the problem of feature selection is not solved by directly implementing mRMR.
Feature selection based on mutual information: criteria ofmax-dependency, max-relevance, and min-redundancy
TL;DR: This work derives an equivalent form, called minimal-redundancy-maximal-relevance criterion (mRMR), for first-order incremental feature selection, and presents a two-stage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers).
Proceedings ArticleDOI
Overview of the face recognition grand challenge
P.J. Phillips,Patrick J. Flynn,T. Scruggs,Kevin W. Bowyer,Jin Chang,K. Hoffman,J. Marques,Jaesik Min,William J. Worek +8 more
TL;DR: The face recognition grand challenge (FRGC) is designed to achieve this performance goal by presenting to researchers a six-experiment challenge problem along with data corpus of 50,000 images.
A 3D Facial Expression Database For Facial Behavior Research.
TL;DR: This is the first attempt at making a 3D facial expression database available for the research community, with the ultimate goal of fostering the research on affective computing and increasing the general understanding of facial behavior and the fine 3D structure inherent in human facial expressions.