Title :
Eye state detection based on nonnegative sparse coding feature
Author :
Chen Siyao ; Qin Jianzhao
Author_Institution :
Smart Cities (Hong Kong) Ltd., Hong Kong, China
Abstract :
It is very useful to detect our eye open or close state in some sistuations. For example, it will give much help to the drivers for driving with drowsiness. In this paper, we propose an efficient method which is made up of four steps for eye state detection: Eye Localization, Preprocessing, Nonnegative sparse coding feature, SVM classifier. We compared our method to other methods[6][7] in our collected dataset which contains the eyes with glasses or in darkness, and so on. In our method, we will preprocess the image for eliminating the illumination and then analyze the eye image feature based on nonnegative sparse coding. It is proved to be very effective in our dataset.
Keywords :
eye; feature extraction; image classification; image coding; object detection; road accidents; support vector machines; traffic engineering computing; SVM classifier; drowsiness driving; eye close state detection; eye image feature analsyis; eye localization; eye open state detection; illumination elimination; image preprocessing; nonnegative sparse coding feature; Encoding; Face; Fatigue; Feature extraction; Image coding; Support vector machines; Vehicles; Eye State; Preprocessing; SVM; Sparse Coding;
Conference_Titel :
Information Science and Technology (ICIST), 2014 4th IEEE International Conference on
Conference_Location :
Shenzhen
DOI :
10.1109/ICIST.2014.6920530