Perceived quality assessment in object-space for animated 3D models
Computational models and methods to handle 3D graphics objects continue to emerge with the wide-range use of 3D models and rapid development of computer graphics technology. Many 3D model modification methods exist to improve computation and transfer time of 3D models in real-time computer graphics applications. Providing user with the least visually-deformed model is essential for 3D modification tasks. In this thesis, we propose a method to estimate the visually perceived differences on animated 3D models. The model makes use of Human Visual System models to mimic visual perception. It can also be used to generate a 3D sensitivity map for a model to act as a guide during the application of modifications. Our approach gives a perceived quality measure using 3D geometric representation by incorporating two factors of Human Visual System (HVS) that contribute to perception of differences. First, spatial processing of human vision model enables us to predict deformations on the surface. Secondly, temporal effects of animation velocity are predicted. Psychophysical experiment data is used for both of these HVS models. We used subjective experiments to verify the validity of our proposed method.