Iranian kinect face database (IKFDB): a color-depth based face database collected by kinect v.2 sensor

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.

Efficient Feature Extraction for Recognition of Human Emotions through Facial Expressions Using Image Processing Algorithms

“…The new technique that has been provided is used for this phase. It is simple to extract features using the Histogram of Oriented Gradient (HOG) algorithm [12], and once color and depth image characteristics have been combined, it is time to utilize Lasso feature selection to condense the data for classification tasks. Finally, each expression is labeled and final matrix is ready for classification using Support Vector Machine(SVM) [13], Multi-Layer Neural Network (MLNN) [14] and Convolution Neural Network (CNN) [14] algorithms.…”

Iranian emotional face database: Acquisition and validation of a stimulus set of basic facial expressions

“…The Iranian Kinect Face Database IKFDB (Mousavi & Mirinezhad, 2021) was published recently as the first dynamic, RGB-D database of Middle Eastern faces.…”