Robust Real-Time Gradient-based Eye Detection and Tracking Using Transform Domain and PSO-Based Feature Selection

Abstract

Despite numerous research on eye detection, this field of study remains challenging due to the individuality of eyes, occlusion, and variability in scale, location, and light conditions. This paper combines a technique of feature extraction and a feature selection method to achieve a significant increase in eye recognition. Subspace methods may improve detection efficiency and accuracy of eye centers detection using dimensionality reduction. In this study, HoG (histogram of Oriented Gradient) descriptor is used to lay the ground for Binary Particle Swarm Optimization (BPSO) based feature selection. HoG features are used for efficient extraction of pose, translation and illumination invariant features. HoG descriptors uses the fact that local object appearance and shape within an image can be described by the distribution of intensity gradients or edge directions. The method upholds invariance to geometric and photometric transformations. The performance of presented method is evaluated using several benchmark datasets, namely, BioID and RS-DMV. Experimental results obtained by applying the proposed algorithm on BioID dataset show that the proposed system outperforms other eye recognition systems. A significant increase in the recognition rate is achieved when using the combination of HoG descriptor, BPSO, and SVM for feature extraction, feature selection and training phase respectively. The Recognition rate for BioID dataset was 99.6% and the detection time was 15.24 msec for every single frame.

Automated Quantification of Eye Blink Rate Using VIOLA–JONES Algorithm

“…Viola-Jonesobjectdetectionframework(Viola&Jones,2004)canbeusedtodetectandtrack objects in real time (Salehi, Keyvanara, & Monadjemi, 2017;Ferhat & Vilariño, 2016). This frameworkisproposedbyPaulViolaandMichaelJonesin2001.Primarily,Viola-Jonesalgorithm specializesinfacedetectionandtracking.Thisalgorithmhasmanycharacteristics:(1)implemented inOpenCVopensourcelibraryascvHaarDetectObjects(),(2)highefficiencyofdetectinganobject ofunknownsize,(3)highefficiencyofdetectinganyfaceinanyimage.Thesecharacteristicsmake itoneofthefamousalgorithmsinimageandvideoprocessing.Therearethreetechniquesofthe Viola-Jonesmethod:…”