TEXTURE ANIMATION MAPPING AND FACIAL EXPRESSION RECOGNITION ON DYNAMIC PROJECTION MAPPING FOR DIGITAL MAKEUP
<p align="justify"> The length of time that it takes for actors to do the turn of face makeup on theatre is one of the problems arising from the entertainment world because an actor can play several different characters in one show. Meanwhile, theatre performances took a quick turn t...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/25002 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | <p align="justify"> The length of time that it takes for actors to do the turn of face makeup on theatre is one of the problems arising from the entertainment world because an actor can play several different characters in one show. Meanwhile, theatre performances took a quick turn to do makeup face. The use of masks is found as solutions to these problems, but the rigid nature of the mask so that the actors facial expressions is limited. To resolve these problems, a solution was made namely digital system for easy makeup cast do a turn of face makeup quickly. Digital makeup system consists of a face tracking, projection mapping, dynamic, animated textures, texture mapping, and identification of gesture and facial expression as a feature of the digital makeup system that serves as the command of the model to do changes in the texture of the animation are shown. In this thesis are described about subsystem mapping textures, texture animation, identification and the facial expressions. UV mapping is selected as the appropriate texture mapping method for digital system makeup, video mapping Unity was chosen as the method to display the texture animation, and the euclidean distance is chosen as a method to identify the expression the face. The results indicate that the mapping of the texture mapping a 2D texture successfully perform on the object model of a 3D human face without any distortion. Texture animation successfully showing animated textures form storytelling on the surface of the 3D face models and can accept the command of the model such as gesture and facial expressions with kesalahan percentage below 5%. Identification of facial expressions can detect four expressions, such as angry, happy, sad, and surprised by using euclidean distance method with accuracy of 94.4%. <p align="justify"> |
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