Animated humanoid characters are a delight to watch. Nowadays they are extensively used in simulators. In military applications animated characters are used for training soldiers, in medical they are used for studying to detect the problems in the joints of a patient, moreover they can be used for instructing people for an event(such as weather forecasts or giving a lecture in virtual environment). In addition to these environments computer games and 3D animation movies are taking the benefit of animated characters to be more realistic. For all of these mediums motion capture data has a great impact because of its speed and robustness and the ability to capture various motions. Motion capture method can be reused to blend various motion styles. Furthermore we can generate more motions from a single motion data by processing each joint data individually if a motion is cyclic. If the motion is cyclic it is highly probable that each joint is defined by combinations of different signals. On the other hand, irrespective of method selected, creating animation by hand is a time consuming and costly process for people who are working in the art side. For these reasons we can use the databases which are open to everyone such as Computer Graphics Laboratory of Carnegie Mellon University.Creating a new motion from scratch by hand by using some spatial tools (such as 3DS Max, Maya, Natural Motion Endorphin or Blender) or by reusing motion captured data has some difficulties. Irrespective of the motion type selected to be animated (cartoonish, caricaturist or very realistic) human beings are natural experts on any kind of motion. Since we are experienced with other peoples’ motions, and comparing each motion to the others, we can easily judge one individual’s mood from his/her body language. As being a natural master of human motions it is very difficult to convince people by a humanoid character’s animation since the recreated motions can include some unnatural artifacts (such as foot-skating, flickering of a joint).
Motion enriching using humanoide captured motions
2010-09-08
Theses
Electronic Resource
English
Àrees temàtiques de la UPC::Informàtica::Infografia , Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo , Computer graphics , Computer animation , Mocap , Motion capture , Motion editing , Inverse kinematics , Motion graphs , Fourier Transform , Signal processing , Quaternions , Blending , Infografia , Animació per ordinador
DDC: | 629 |