A STATE OF THE ART COMPARISON OF DATABASES FOR FACIAL OCCLUSION

2015 ◽  
Vol 77 (13) ◽  
Author(s):  
Abdulganiyu Abdu Yusuf ◽  
Fatma Susilawati Mohamad ◽  
Zahraddeen Sufyanu
Keyword(s):  
Face Detection ◽  
Research Areas ◽  
Level Of Details ◽  
Real World Applications ◽  
In The Wild ◽  
Recording Conditions ◽  
3D Databases ◽  
Face Detection And Recognition ◽  
2D And 3D ◽  
Detection And Recognition

Face recognition continues to be one of the most popular research areas of image processing and computer vision. There are various face databases available to researchers for face detection and recognition. These databases are customized for a particular need of one algorithm. They are range in size, scope, and purpose. Few of these databases from the literature contain face occlusions in several positions of the faces to enable real world applications.  In this paper, we present four different occlusion face databases. These are Aleix-Robert (AR), Bosphorus, Labeled Faces in the Wild (LFW), and University of Milano Bicocca Database (UMB) face databases. At each section, the key features of the database are presented with the recording conditions, though not all of them are discussed at the same level of details. Detailed comparisons of the databases were made based on controlled and uncontrolled databases, 2D and 3D databases and also their uniqueness. Comparison was also made with other databases out of the categorization mentioned. The databases are useful for performing a rigorous benchmarking of face detection and recognition algorithms.

A Novel Approach of Face Detection Based on Skin Color Segmentation and SVM

2011 ◽  
Vol 225-226 ◽  
pp. 437-441
Author(s):  
Jing Zhang ◽  
You Li
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Information Access ◽  
Color Segmentation ◽  
Support Vector ◽  
Svm Classifier ◽  
Novel Approach ◽  
Great Performance ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Nowadays, face detection and recognition have gained importance in security and information access. In this paper, an efficient method of face detection based on skin color segmentation and Support Vector Machine(SVM) is proposed. Firstly, segmenting image using color model to filter candidate faces roughly; And then Eye-analogue segments at a given scale are discovered by finding regions which are darker than their neighborhoods to filter candidate faces farther; at the end, SVM classifier is used to detect face feature in the test image, SVM has great performance in classification task. Our tests in this paper are based on MIT face database. The experimental results demonstrate that the proposed method is encouraging with a successful detection rate.

Hybrid HOG-SVM encrypted face detection and recognition model

2022 ◽  
pp. 1-14
Author(s):  
Shilpa Sharma ◽  
Linesh Raja ◽  
Vaibhav Bhatnagar ◽  
Divya Sharma ◽  
Swami Nisha Bhagirath ◽  
...  
Keyword(s):  
Face Detection ◽  
Recognition Model ◽  
Face Detection And Recognition ◽  
Detection And Recognition
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