| 摘要 |
PURPOSE: A facial expression recognizing method and a system thereof are provided to enhance regional spatial characteristics and weaken information of shapes which include unnecessary information by applying a DoG(Difference of Gaussian) kernel to an image applied with an AAM(active appearance model). CONSTITUTION: A DoG kernel(514) convolutes an input image. An AAM unit(516) extracts a facial area from the convoluted image, extracts an appearance and shape parameter from the facial area, and converts an AAM based on face feature elements in order to combine the AAM with the facial area. The AAM unit recognizes a facial expression by updating the appearance and shape parameter and the image forming the facial area to which a synthetic face image is inputted. An EFM(Enhanced Fisher Model) classifier(518) processes the appearance and shape parameter through an EFM classifying method. [Reference numerals] (510) Camera; (512) Image pre-processing unit; (514) DOG kernel; (516) AAM modeling unit; (518) EFM classifier; (520) Display unit; (522) Database
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