A study on Application of Human Face Recognition to Protect VDT User''s Eyes

• Main Authors: Jau-Wei Ho, 何肇偉
• Other Authors: Jung-Tang Huang
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/52882412930835746712

碩士 === 國立臺北科技大學 === 機電整合研究所 === 90 === In this study, a system that can actively remind the VDT''s user to let his/her eyes take a break has been developed. The system uses a built-in timer to record how long the VDT user has been continuously working on the computer, and a PC camera on top of the computer monitor to simultaneously keep capturing the image of the VDT user and the environment as well. In order to objectively estimate how long a person continuously uses the computer, the developed system can determine whether the same person keeps using the computer through face recognition technology. It can detect the visual distance and eye''s blinking by the facial feature information. If the user doesn''t keep a proper visual distance, or his/her eyes blink too often or too less, or has continuously been using the computer for a long time, the system will pop up a warning message in words/picture/voice to the user. Therefore, this developed system can initiatively protect VDT user''s eyes. This study applies face detection, face recognition, visual distance and eye''s blinking detection. Regarding the face detection, a self-calibration algorithm of has been presented to eliminate the influence of color image caused by the light source of environment. Then, skin extraction and creating a skin window are followed to find the skin region of the image. Each skin region has to be checked to identify human face so as to complete the process of face detection. In face recognition, the image of face window is equalized by the technique of image process. The facial feature, then, can be extracted by combining edge detection and binary process. According to the features of the binary image, the central line of the face part can be determined. Then, the mouth and eyes region cam be extracted along the central line and whether the user wearing glasses can also be identified. Three distinct feature regions are taken from the mouth and eyes parts in order to identify whether the same user is using the computer by the template matching method. Regarding the visual distance, the distance is detected by the width of user''s face. In the eye''s blinking detection, the movement operation of face elements is carefully tracked to detect user''s eye blinking. How exhausted of the user''s eyes is, then, estimated by the eye''s blinking per minute.