scholarly journals Automatic 3D Face Detection, Normalization and Recognition

2006 ◽  
Author(s):  
Ajmal Mian ◽  
Mohammed Bennamoun ◽  
Robyn Owens
Keyword(s):  
Face Detection ◽  
3D Face

3D face detection based on salient features extraction and skin colour detection using data mining

2017 ◽  
Vol 65 (7) ◽  
pp. 393-408 ◽  
Author(s):  
Abdul Rahman El Sayed ◽  
Abdallah El Chakik ◽  
Hassan Alabboud ◽  
Adnan Yassine
Keyword(s):  
Data Mining ◽  
Face Detection ◽  
Features Extraction ◽  
Skin Colour ◽  
3D Face ◽  
Salient Features ◽  
Using Data

3D Face Detection via Reconstruction Over Hierarchical Features for Single Face Situations

2016 ◽  
Vol 30 (04) ◽  
pp. 1655013
Author(s):  
Bo Yu ◽  
Ian Lane ◽  
Fang Chen
Keyword(s):  
Real Time ◽  
Face Detection ◽  
Rejection Rate ◽  
Input Image ◽  
Computationally Efficient ◽  
3D Face ◽  
3D Data ◽  
Single Face ◽  
Multiple Challenges ◽  
Face Datasets

There are multiple challenges in face detection, including illumination conditions and diverse poses of the user. Prior works tend to detect faces by segmentation at pixel level, which are generally not computationally efficient. When people are sitting in the car, which can be regarded as single face situations, most face detectors fail to detect faces under various poses and illumination conditions. In this paper, we propose a simple but efficient approach for single face detection. We train a deep learning model that reconstructs face directly from input image by removing background and synthesizing 3D data for only the face region. We apply the proposed model to two public 3D face datasets, and obtain significant improvements in false rejection rate (FRR) of 4.6% (from 4.6% to 0.0%) and 21.7% (from 30.2% to 8.5%), respectively, compared with state-of-art performances in two datasets. Furthermore, we show that our reconstruction approach can be applied using 1/2 the time of a widely used real-time face detector. These results demonstrate that the proposed Reconstruction ConNet (RN) is both more accurate and efficient for real-time face detection than prior works.

3D face detection using transform invariant features

2010 ◽  
Vol 46 (13) ◽  
pp. 905 ◽  
Author(s):  
E. Akagündüz ◽  
I. Ulusoy
Keyword(s):  
Face Detection ◽  
3D Face ◽  
Invariant Features

A Novel Method for 3D Face Detection and Normalization

2007 ◽  
Vol 2 (5) ◽  
Author(s):  
Robert Niese ◽  
Ayoub Al-Hamadi ◽  
Bernd Michaelis
Keyword(s):  
Face Detection ◽  
3D Face ◽  
Novel Method

A3FD: Accurate 3D Face Detection

2008 ◽  
pp. 155-165 ◽  
Author(s):  
Marco Anisetti ◽  
Valerio Bellandi ◽  
Ernesto Damiani ◽  
Luigi Arnone ◽  
Benoit Rat
Keyword(s):  
Face Detection ◽  
3D Face

Gappy PCA Classification for Occlusion Tolerant 3D Face Detection

2009 ◽  
Vol 35 (3) ◽  
pp. 193-207 ◽  
Author(s):  
Alessandro Colombo ◽  
Claudio Cusano ◽  
Raimondo Schettini
Keyword(s):  
Face Detection ◽  
3D Face

Learning-based 3D face detection using geometric context

2007 ◽  
Vol 18 (4-5) ◽  
pp. 483-492 ◽  
Author(s):  
Yanwen Guo ◽  
Fuyan Zhang ◽  
Chunxiao Liu ◽  
Hanqiu Sun ◽  
Qunsheng Peng
Keyword(s):  
Face Detection ◽  
3D Face ◽  
Geometric Context

3D face detection using curvature analysis

2006 ◽  
Vol 39 (3) ◽  
pp. 444-455 ◽  
Author(s):  
Alessandro Colombo ◽  
Claudio Cusano ◽  
Raimondo Schettini
Keyword(s):  
Face Detection ◽  
3D Face ◽  
Curvature Analysis
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