The mapping of images onto surfaces may substantially increase the realism and information content of computer-generated imagery. The projection of a flat source image onto a curved surface may involve sampling difficulties, however, which are compounded as the view of the surface changes. As the projected scale of the surface increases, interpolation between the original samples of the source image is necessary; as the scale is reduced, approximation of multiple samples in the source is required. Thus a constantly changing sampling window of view-dependent shape must traverse the source image. To reduce the computation implied by these requirements, a set of prefiltered source images may be created. This approach can be applied to particular advantage in animation, where a large number of frames using the same source image must be generated. This paper advances a "pyramidal parametric " prefiltering and sampling geometry which minimizes aliasing effects and assures continuity within and between target images. Although the mapping of texture onto surfaces is an excellent example of the process and provided the original motivation for its development, pyramidal parametric data structures admit of wider application. The aliasing of not only surface texture, but also highlights and even the surface representations themselves, may be minimized by pyramidal parametric means.

Abstract 1 Domain-specific generators will increasingly rely on graphical languages for declarative specifications of target applications. Such languages will provide front-ends to generators and related tools to produce customized code on demand. Critical to the success of this approach will be domain-specific design wizards, tools that guide users in their selection of components for constructing particular applications. In this paper, we present the P3 ContainerStore graphical language, its generator, and design wizard. 1

Constraint programming techniques have proven their efficiency in solving high combinatory problems. In this paper, we study the adaptation, the extension and the limits of those techniques in the space planning problem which consists in finding the locations and the sizes of several objects under geometric constraints in a location space. For all that, we define the formalism of Geometric Constraint Satisfaction Problem (GCSP) with geometric domains for representing the position variables of the objects. We propose in particular an intelligent and geometric backtrack based on constraint propagations. Then we present our environment dedicated to problems with rectangles of variable sizes. Keywords: Space planning, constraint programming, geometric constraints, placement, partitioning, CSP. 1 Introduction Space planning problems include object placement problem (e.g. room arrangement) , space partitioning problem (e.g. floor plan of an apartment), cuttingstock problems and placement/r...

Abstract. We are here dealing with the problem of space layout planning. We present an approach based on an intermediate topological level with dynamic space ordering (dso) heuristics. Our software ARCHiPLAN proceeds through a number of steps. First, all the topologically different solutions, without presuming any precise dimension, are enumerated. Next, we may evolve in this topological solution space, and than refine some of them to form consistent geometrical solutions. For each topological solution chosen, the optimising geometrical solution is determined from a cost, useful surface or wall length. By using dynamic space ordering heuristics in the topological level the enumeration time has been reduced.

Typical instances, that is, instances that are representative for a particular situation or concept, play an important role in human knowledge representation and reasoning, in particular in analogical reasoning. This well-known observation has been a motivation for investigations in cognitive psychology which provide a basis for our characterization of typical instances within concept structures and for a new inference rule for justified analogical reasoning with typical instances. In a nutshell this paper suggests to augment the propositional knowledge representation system by a non-propositional part consisting of concept structures which may have directly represented instances as elements. The traditional reasoning system is extended by a rule for justified analogical inference with typical instances using information extracted from both knowledge representation subsystems. Keywords: analogical reasoning, typical instance, hybrid knowledge representation 1 Introduction The traditio...

Embracing complexity in design is one of the critical issues and challenges of the 21 st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr). The purpose of the cluster is to create a research community and propose a research agenda on the relation between complexity and design. The hypothesis of the cluster is that complexity exists across every aspect of design, including:

Designing plans: a control