L-systems in Geometric Modeling

We show that parametric context-sensitive L-systems with affine geometry interpretation provide a succinct description of some of the most fundamental algorithms of geometric modeling of curves. Examples include the Lane-Riesenfeld algorithm for generating B-splines, the de Casteljau algorithm for generating Bezier curves, and their extensions to rational curves. Our results generalize the previously reported geometric-modeling applications of L-systems, which were limited to subdivision curves.Comment: In Proceedings DCFS 2010, arXiv:1008.127

A theoretical reflection on smart shape modeling

This paper presents, as far as the authors are aware, a complete and extended new taxonomy of shape specification modeling techniques and a characterization of shape design systems, all based on the relationship of users’ knowledge to the modeling system they use to generate shapes. In-depth knowledge of this relationship is not usually revealed in the regular university training courses such as bachelor’s, master’s and continuing education. For this reason, we believe that it is necessary to modify the learning process, offering a more global vision of all the currently existing techniques and extending training in those related to algorithmic modeling techniques. We consider the latter to be the most powerful current techniques for modeling complex shapes that cannot be modeled with the usual techniques known to date. Therefore, the most complete training should include everything from the usual geometry to textual programming. This would take us a step further along the way to more powerful design environments. The proposed taxonomy could serve as a guideline to help improve the learning process of students and designers in a complex environment with increasingly powerful requirements and tools. The term “smart” is widely used nowadays, e.g. smart phones, smart cars, smart homes, smart cities... and similar terms such as “smart shape modeling”. Nowadays, the term smart is applied from a marketing point of view, whenever an innovation is used to solve a complex problem. This is the case for what is currently called smart shape modeling. However, in the future; this concept should mean a much better design environment than today. The smart future requires better trained and skilled engineers, architects, designers or technical students. This means that they must be prepared to be able to contribute to the creation of new knowledge, to the use of innovations to solve complex problems of form, and to the extraction of the relevant pieces of intelligence from the growing volume of knowledge and technologies accessible today. Our taxonomy is presented from the point of view of methods that are possibly furthest away from what is considered today as “intelligent shape modeling” to the limit of what is achievable today and which the authors call “Generic Shape Algorithm”. Finally, we discuss the characteristics that a shape modeling system must have to be truly “intelligent”: it must be “proactive” in applying innovative ideas to achieve a solution to a complex problem

Generalized Debye Sources Based EFIE Solver on Subdivision Surfaces

The electric field integral equation is a well known workhorse for obtaining fields scattered by a perfect electric conducting (PEC) object. As a result, the nuances and challenges of solving this equation have been examined for a while. Two recent papers motivate the effort presented in this paper. Unlike traditional work that uses equivalent currents defined on surfaces, recent research proposes a technique that results in well conditioned systems by employing generalized Debye sources (GDS) as unknowns. In a complementary effort, some of us developed a method that exploits the same representation for both the geometry (subdivision surface representations) and functions defined on the geometry, also known as isogeometric analysis (IGA). The challenge in generalizing GDS method to a discretized geometry is the complexity of the intermediate operators. However, thanks to our earlier work on subdivision surfaces, the additional smoothness of geometric representation permits discretizing these intermediate operations. In this paper, we employ both ideas to present a well conditioned GDS-EFIE. Here, the intermediate surface Laplacian is well discretized by using subdivision basis. Likewise, using subdivision basis to represent the sources, results in an efficient and accurate IGA framework. Numerous results are presented to demonstrate the efficacy of the approach

THE REALISM OF ALGORITHMIC HUMAN FIGURES A Study of Selected Examples 1964 to 2001

It is more than forty years since the first wireframe images of the Boeing Man revealed a stylized hu-man pilot in a simulated pilot's cabin. Since then, it has almost become standard to include scenes in Hollywood movies which incorporate virtual human actors. A trait particularly recognizable in the games industry world-wide is the eagerness to render athletic muscular young men, and young women with hour-glass body-shapes, to traverse dangerous cyberworlds as invincible heroic figures. Tremendous efforts in algorithmic modeling, animation and rendering are spent to produce a realistic and believable appearance of these algorithmic humans. This thesis develops two main strands of research by the interpreting a selection of examples. Firstly, in the computer graphics context, over the forty years, it documents the development of the creation of the naturalistic appearance of images (usually called photorealism ). In particular, it de-scribes and reviews the impact of key algorithms in the course of the journey of the algorithmic human figures towards realism . Secondly, taking a historical perspective, this work provides an analysis of computer graphics in relation to the concept of realism. A comparison of realistic images of human figures throughout history with their algorithmically-generated counterparts allows us to see that computer graphics has both learned from previous and contemporary art movements such as photorealism but also taken out-of-context elements, symbols and properties from these art movements with a questionable naivety. Therefore, this work also offers a critique of the justification of the use of their typical conceptualization in computer graphics. Although the astounding technical achievements in the field of algorithmically-generated human figures are paralleled by an equally astounding disregard for the history of visual culture, from the beginning 1964 till the breakthrough 2001, in the period of the digital information processing machine, a new approach has emerged to meet the apparently incessant desire of humans to create artificial counterparts of themselves. Conversely, the theories of traditional realism have to be extended to include new problems that those active algorithmic human figures present

Parametric Surfaces for Augmented Architecture representation

Augmented Reality (AR) represents a growing communication channel, responding to the need to expand reality with additional information, offering easy and engaging access to digital data. AR for architectural representation allows a simple interaction with 3D models, facilitating spatial understanding of complex volumes and topological relationships between parts, overcoming some limitations related to Virtual Reality. In the last decade different developments in the pipeline process have seen a significant advancement in technological and algorithmic aspects, paying less attention to 3D modeling generation. For this, the article explores the construction of basic geometries for 3D model’s generation, highlighting the relationship between geometry and topology, basic for a consistent normal distribution. Moreover, a critical evaluation about corrective paths of existing 3D models is presented, analysing a complex architectural case study, the virtual model of Villa del Verginese, an emblematic example for topological emerged problems. The final aim of the paper is to refocus attention on 3D model construction, suggesting some "good practices" useful for preventing, minimizing or correcting topological problems, extending the accessibility of AR to people engaged in architectural representation

QuickCSG: Fast Arbitrary Boolean Combinations of N Solids

QuickCSG computes the result for general N-polyhedron boolean expressions without an intermediate tree of solids. We propose a vertex-centric view of the problem, which simplifies the identification of final geometric contributions, and facilitates its spatial decomposition. The problem is then cast in a single KD-tree exploration, geared toward the result by early pruning of any region of space not contributing to the final surface. We assume strong regularity properties on the input meshes and that they are in general position. This simplifying assumption, in combination with our vertex-centric approach, improves the speed of the approach. Complemented with a task-stealing parallelization, the algorithm achieves breakthrough performance, one to two orders of magnitude speedups with respect to state-of-the-art CPU algorithms, on boolean operations over two to dozens of polyhedra. The algorithm also outperforms GPU implementations with approximate discretizations, while producing an output without redundant facets. Despite the restrictive assumptions on the input, we show the usefulness of QuickCSG for applications with large CSG problems and strong temporal constraints, e.g. modeling for 3D printers, reconstruction from visual hulls and collision detection