Jin-Keun Dong

Faculty-supervised measurements of the face and of mandibular movements on young adults

PURPOSE The purpose of this study was to determine the average facial proportions and mandibular movement capacity of 316 first-year dental students who carefully recorded them on each other. MATERIALS AND METHODS This early exacting clinical experience was closely supervised by the authors in Columbus, Ohio during 1969-70. Five vertical and six horizontal distances were measured on each subjects face. An ala-tragus line and an occlusal line were drawn on the left side of the face to determine if these two lines were parallel. Measurements of mandibular movements involved maximum normal and hinge opening at the incisors and maximum amounts of right, left lateral and protrusive excursions of the mandible. RESULTS The ala width and distance between the tips of upper right and left canine cusps averaged (35.2 mm and 34.8 mm) but with very large individual variations. The distance between ala to occlusal plane lines was 29.9 mm at the tragus and 31.3 mm near the ala. The angle between orbitale and ala-tragus averaged 13.6 degrees. CONCLUSION The upper lip length was the most variable and the distance between the pupils was the most stable of the eleven facial measurements. The ala-tragus line and the occlusal plane lines were for all practical purposes parallel. Maximum jaw opening averaged 51.2 mm which was 3.0 times larger than maximal hinge opening of 17.2 mm. The maximum right plus left side jaw excursions (9.2 and 9.4 mm) totaled 18.6 mm, 2.3 times more than the 8.0 mm mean maximum forward protrusion.

Detection of Lip Area and Smile Analysis for Self Smile Training

In this study, we propose an automated smile analysis system for self smile training. The proposed system detects face area from the input image with the AdaBoost algorithm. It then identifies facial features based on the face shape model generated by using ASM(Active Shape Model). Once facial features of the face are identified, the lip line and teeth area necessary for smile analysis are detected. An analysis of the lip line and individual teeth areas allows for an automated analysis of smiling degree of users, enabling users to check their smiling degree on a real time basis. The developed system exhibited an average error of 0.7 compared to previous smile analysis results released by dental clinics for smile training, and it is expected to be used directly by users for smile training.