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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/28671

Title: 人眼九宮格注視方位之辨識研究
Authors: 陳冠同;曾敬翔
Contributors: NTOU:Department of Electrical Engineering
Keywords: gesture recognition;face recognition;eye-gaze direction
Date: 2009
Issue Date: 2011-10-21T02:39:04Z
Publisher: 數位科技與創新管理研討會論文集
Abstract: 摘要:由於現代生活對智慧型人機等介面需求的增加,姿態辨識的運用也日益普遍,從目前當紅的遊戲機Wii 到防盜系統的人臉辨識都是姿態辨識應用的例子。眼睛注視方位的辨識也是姿態辨識裡面的一項運用,它可以用在偵測到駕駛者閉眼打瞌睡或精神不振,並適時的發出警告聲響這將有助於減少許多交通事故的發生。本論文的研究目標主要是從人臉的視訊訊號中辨識出人眼的注視方位。這可以用在監視駕駛人狀態及互動式視訊遊戲。我們將輸入的整張影像利用膚色的特性擷取出正確的人臉區塊,再從人臉的區塊中去偵測精確的眼睛邊框位置並擷取出來,最後,經由對眼珠的偵測以及眼睛注視不同方位所呈現出來的特有條件,對注視的不同方位來加以辨識。本研究資料庫包含99 張實驗用的影像,影像中人臉之注視方位包括九個方位(分別為:右下、右、右上、下、直視、上方、左下、左以及左上方)。實驗結果顯示所提出的辨識方法可達到93.94%的辨識率。凡涉及人眼注視方位之互動式人機介面皆能因本研究成果而獲益。
Abstract:The demands for intelligent man-machine interfaces in modern life have made the application of gesture recognition become more and more popular. For example, recognizing human motions in video games (such as the Wii from the Nintendo) and recognizing human faces in security systems are applications of the gesture recognition. Recognition of the eye-gaze direction is an important task in gesture recognition, it can be use to monitor the status of a vehicle driver. By detecting the driver’s drowsy condition and issuing an alert to the driver, lots of potential accidents due to insecure driving can be avoided. The main goal of this paper is to recognize the eye-gaze direction from video signals of human faces. This can be used in vehicle driver monitoring and interactive video games. We use the color of skin to identify the face area in the image, then locate the eye sockets with an algorithm. Finally, we detect the locations of the pupils within the eye sockets and then use this feature to recognize the eye-gaze direction. In this study, 99 images are extracted from the video signal collected via a web camera. These images contain human faces gazing at 9 different directions (lower right, right, upper right, down, straight, up, lower left, left, upper left). Experimental result indicates that the proposed method can recognize the 9 directions with a recognition rate of 93.94%. Interactive man-machine interfaces which involve eye-gaze directions can benefit from the reseach result.
Relation: pp.500-511
URI: http://ntour.ntou.edu.tw/handle/987654321/28671
Appears in Collections:[電機工程學系] 演講及研討會

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