In this paper an efficient framework for the creation of 3D digital contentwith point sampled ge-ometry is proposed. A new hierarchy of shape representations with three levelsis adopted in this framework. Based on thi...In this paper an efficient framework for the creation of 3D digital contentwith point sampled ge-ometry is proposed. A new hierarchy of shape representations with three levelsis adopted in this framework. Based on this new hierarchical shape representation, the proposedframework offers concise integration of various volumetric- and surface-based modeling techniques,such as Boolean operation, offset, blending, free-form defor-mation, parameterization and texturemapping, and thus simplifies the complete modeling process. Previously to achieve the same goal,several separated algorithms had to be used independently with inconsistent volumetric and surfacerepresentations of the free-form object. Both graphics and industrial applications are presented todemonstrate the effectiveness and efficiency of the proposed framework.展开更多
When we think of an object in a supervised learn- ing setting, we usually perceive it as a collection of fixed at- tribute values. Although this setting may be suited well for many classification tasks, we propose a n...When we think of an object in a supervised learn- ing setting, we usually perceive it as a collection of fixed at- tribute values. Although this setting may be suited well for many classification tasks, we propose a new object repre- sentation and therewith a new challenge in data mining; an object is no longer described by one set of attributes but is represented in a hierarchy of attribute sets in different levels of quality. Obtaining a more detailed representation of an ob- ject comes with a cost. This raises the interesting question of which objects we want to enhance under a given budget and cost model. This new setting is very useful whenever re- sources like computing power, memory or time are limited. We propose a new active adaptive algorithm （AAA） to im- prove objects in an iterative fashion. We demonstrate how to create a hierarchical object representation and prove the ef- fectiveness of our new selection algorithm on these datasets.展开更多
文摘In this paper an efficient framework for the creation of 3D digital contentwith point sampled ge-ometry is proposed. A new hierarchy of shape representations with three levelsis adopted in this framework. Based on this new hierarchical shape representation, the proposedframework offers concise integration of various volumetric- and surface-based modeling techniques,such as Boolean operation, offset, blending, free-form defor-mation, parameterization and texturemapping, and thus simplifies the complete modeling process. Previously to achieve the same goal,several separated algorithms had to be used independently with inconsistent volumetric and surfacerepresentations of the free-form object. Both graphics and industrial applications are presented todemonstrate the effectiveness and efficiency of the proposed framework.
文摘When we think of an object in a supervised learn- ing setting, we usually perceive it as a collection of fixed at- tribute values. Although this setting may be suited well for many classification tasks, we propose a new object repre- sentation and therewith a new challenge in data mining; an object is no longer described by one set of attributes but is represented in a hierarchy of attribute sets in different levels of quality. Obtaining a more detailed representation of an ob- ject comes with a cost. This raises the interesting question of which objects we want to enhance under a given budget and cost model. This new setting is very useful whenever re- sources like computing power, memory or time are limited. We propose a new active adaptive algorithm （AAA） to im- prove objects in an iterative fashion. We demonstrate how to create a hierarchical object representation and prove the ef- fectiveness of our new selection algorithm on these datasets.
