Perceptual information-theoretic measures for viewpoint selection and object recognition

Texto Completo
Compartir
Viewpoint selection has been an emerging area in computer graphics for some years, and it is now getting maturity with applications in fields such as scene navigation, volume visualization, object recognition, mesh simplification, and camera placement. But why is viewpoint selection important? For instance, automated viewpoint selection could play an important role when selecting a representative model by exploring a large 3D model database in as little time as possible. Such an application could show the model view that allows for ready recognition or understanding of the underlying 3D model. An ideal view should strive to capture the maximum information of the 3D model, such as its main characteristics, parts, functionalities, etc. The quality of this view could affect the number of models that the artist can explore in a certain period of time. In this thesis, we present an information-theoretic framework for viewpoint selection and object recognition. From a visibility channel between a set of viewpoints and the polygons of a 3D model we obtain several viewpoint quality measures from the respective decompositions of mutual information. We also review and compare in a common framework the most relevant viewpoint quality measures for polygonal models presented in the literature. From the information associated to the polygons of a model, we obtain several shading approaches to improve the object recognition and the shape perception. We also use this polygonal information to select the best views of a 3D model and to explore it. We use these polygonal information measures to enhance the visualization of a 3D terrain model generated from textured geometry coming from real data. Finally, we analyze the application of the viewpoint quality measures presented in this thesis to compute the shape similarity between 3D polygonal models. The information of the set of viewpoints is seen as a shape descriptor of the model. Then, given two models, their similarity is obtained by performing a registration process between the corresponding set of viewpoints ​
​L'accés als continguts d'aquesta tesi queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: http://creativecommons.org/licenses/by-nc-sa/3.0/es/