DETECTION AND TRACKING OF FACIAL FEATURES BY USING EDGE PIXEL COUNTING AND DEFORMABLE CIRCULAR TEMPLATE MATCHING

In this paper face feature detection and tracking are discussed, using methods called edge pixel counting and deformable circular template m atching. Instead of utilizing color or gray scale information of the f acial image, the proposed edge pixel counting method utilizes the edge information to estimate the face Feature positions such as eyes, nose and mouth, using a variable size face feature template, the initial s ize of which is predetermined by using a facial image database. The me thod is robust in the sense that the detection is possible with facial images with different skin color and different facial orientations. S ubsequently, by using a deformable circular template matching two iris positions of the face are determined and are used in the edge pixel c ounting, to track the features in the next frame. Although feature tra cking using gray scale template matching often fails when inter frame correlation around the feature areas are very low due to facial expres sion change (such as, talking, smiling, eye blinking etc.), feature tr acking using edge pixel counting can track facial features reliably. S ome experimental results are shown to demonstrate the effectiveness of the proposed method.