Iranian kinect face database (IKFDB): a color-depth based face database collected by kinect v.2 sensor
Open Access
- 7 January 2021
- journal article
- research article
- Published by Springer Nature in SN Applied Sciences
- Vol. 3 (1) , 1-17
Abstract
This study presents a new color-depth based face database gathered from different genders and age ranges from Iranian subjects. Using suitable databases, it is possible to validate and assess available methods in different research fields. This database has application in different fields such as face recognition, age estimation and Facial Expression Recognition and Facial Micro Expressions Recognition. Image databases based on their size and resolution are mostly large. Color images usually consist of three channels namely Red, Green and Blue. But in the last decade, another aspect of image type has emerged, named “depth image”. Depth images are used in calculating range and distance between objects and the sensor. Depending on the depth sensor technology, it is possible to acquire range data differently. Kinect sensor version 2 is capable of acquiring color and depth data simultaneously. Facial expression recognition is an important field in image processing, which has multiple uses from animation to psychology. Currently, there is a few numbers of color-depth (RGB-D) facial micro expressions recognition databases existing. With adding depth data to color data, the accuracy of final recognition will be increased. Due to the shortage of color-depth based facial expression databases and some weakness in available ones, a new and almost perfect RGB-D face database is presented in this paper, covering Middle-Eastern face type. In the validation section, the database will be compared with some famous benchmark face databases. For evaluation, Histogram Oriented Gradients features are extracted, and classification algorithms such as Support Vector Machine, Multi-Layer Neural Network and a deep learning method, called Convolutional Neural Network or are employed. The results are so promising.Keywords
This publication has 38 references indexed in Scilit:
- Static and dynamic 3D facial expression recognition: A comprehensive surveyImage and Vision Computing, 2012
- Automated Facial Action Coding System for dynamic analysis of facial expressions in neuropsychiatric disordersJournal of Neuroscience Methods, 2011
- Face detection evaluation: a new approach based on the golden ratio ${\Phi}$Signal, Image and Video Processing, 2011
- Lie Catching and Microexpressions2009
- Detecting Deception from Emotional and Unemotional CuesJournal of Nonverbal Behavior, 2008
- Are Loss Functions All the Same?Neural Computation, 2004
- Robust Real-Time Face DetectionInternational Journal of Computer Vision, 2004
- Face detection in color imagesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
- Recognizing action units for facial expression analysisIEEE Transactions on Pattern Analysis and Machine Intelligence, 2001
- Detection of Postnatal DepressionThe British Journal of Psychiatry, 1987