| Summary: | 碩士 === 國立臺灣師範大學 === 資訊工程學系 === 101 === Eye state recognition is an important technology in the computer vision. It can be developed to variety applications. Most eye state recognition is pure background, short distance, and the head does not shack. Due to the application in the general classroom that is light interference and long distance, the purpose of our research is to recognize the eye state quickly and effectively.
Our method is divided into three parts, face detection, eye region decision, and eye state recognition. First is to find out the face image and do the pre-processing, then make use of the area of interest (AOI) to get the roughly eye position, the last step is utilizing the horizontal projection and vertical projection to get the precise eye position. Eye state recognition is using our proposed method that is a new way to extract feature from binary image and work with SVM model to determine the eye state.
The experiment shows that our proposed method that is a new way to extract feature from binary image is better than complexity function method. And our method is not only performs well in the recognition rate but also in the execution time that is 1.5~3 times faster than SVM method.
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