Image Sampling with Quasicrystals

We investigate the use of quasicrystals in image sampling. Quasicrystals produce space-filling, non-periodic point sets that are uniformly discrete and relatively dense, thereby ensuring the sample sites are evenly spread out throughout the sampled image. Their self-similar structure can be attractive for creating sampling patterns endowed with a decorative symmetry. We present a brief general overview of the algebraic theory of cut-and-project quasicrystals based on the geometry of the golden ratio. To assess the practical utility of quasicrystal sampling, we evaluate the visual effects of a variety of non-adaptive image sampling strategies on photorealistic image reconstruction and non-photorealistic image rendering used in multiresolution image representations. For computer visualization of point sets used in image sampling, we introduce a mosaic rendering technique.Comment: For a full resolution version of this paper, along with supplementary materials, please visit at http://www.Eyemaginary.com/Portfolio/Publications.htm

Holistic corpus-based dialectology

This paper is concerned with sketching future directions for corpus-based dialectology. We advocate a holistic approach to the study of geographically conditioned linguistic variability, and we present a suitable methodology, 'corpusbased dialectometry', in exactly this spirit. Specifically, we argue that in order to live up to the potential of the corpus-based method, practitioners need to (i) abandon their exclusive focus on individual linguistic features in favor of the study of feature aggregates, (ii) draw on computationally advanced multivariate analysis techniques (such as multidimensional scaling, cluster analysis, and principal component analysis), and (iii) aid interpretation of empirical results by marshalling state-of-the-art data visualization techniques. To exemplify this line of analysis, we present a case study which explores joint frequency variability of 57 morphosyntax features in 34 dialects all over Great Britain

Clustering-Based Robot Navigation and Control

In robotics, it is essential to model and understand the topologies of configuration spaces in order to design provably correct motion planners. The common practice in motion planning for modelling configuration spaces requires either a global, explicit representation of a configuration space in terms of standard geometric and topological models, or an asymptotically dense collection of sample configurations connected by simple paths. In this short note, we present an overview of our recent results that utilize clustering for closing the gap between these two complementary approaches. Traditionally an unsupervised learning method, clustering offers automated tools to discover hidden intrinsic structures in generally complex-shaped and high-dimensional configuration spaces of robotic systems. We demonstrate some potential applications of such clustering tools to the problem of feedback motion planning and control. In particular, we briefly present our use of hierarchical clustering for provably correct, computationally efficient coordinated multirobot motion design, and we briefly describe how robot-centric Voronoi diagrams can be used for provably correct safe robot navigation in forest-like cluttered environments, and for provably correct collision-free coverage and congestion control of heterogeneous disk-shaped robots.For more information: Kod*la

Functionally heterogeneous porous scaffold design for tissue engineering

Most of the current tissue scaffolds are mainly designed with homogeneous porosity which does not represent the spatial heterogeneity found in actual tissues. Therefore engineering a realistic tissue scaffolds with properly graded properties to facilitate the mimicry of the complex elegance of native tissues are critical for the successful tissue regeneration. In this work, novel bio-mimetic heterogeneous porous scaffolds have been modeled. First, the geometry of the scaffold is extracted along with its internal regional heterogeneity. Then the model has been discretized with planner slices suitable for layer based fabrication. An optimum filament deposition angle has been determined for each slice based on the contour geometry and the internal heterogeneity. The internal region has been discritized considering the homogeneity factor along the deposition direction. Finally, an area weight based approach has been used to generate the spatial porosity function that determines the filament deposition location for desired biomimetic porosity. The proposed methodology has been implemented and illustrative examples are provided. The effective porosity has been compared between the proposed design and the conventional homogeneous scaffolds. The result shows a significant error reduction towards achieving the biomimetic porosity in the scaffold design and provides better control over the desired porosity level. Moreover, sample designed structures have also been fabricated with a NC motion controlled micro-nozzle biomaterial deposition system

Spherical layout implementation using centroidal voronoi tessellations

The 3D tree visualization faces multiple challenges: the election of an appropriate layout, the use of the interactions that make the data exploration easier and a metaphor that helps in the process of information understanding. A good combination of these elements will result in a visualization that effectively conveys the key features of a complex structure or system to a wide range of users and permits the analytical reasoning process. In previous works we presented the Spherical Layout, a technique for 3D tree visualization that provides an excellent base to achieve those key features. The layout was implemented using the Tri- Sphere algorithm, a method that discretized the spheres's surfaces with triangles to achieve a uniform distribution of the nodes. The goal of this work was centered in a new algorithm for the implementation of the Spherical layout; we called it the Spherical Centroidal Voronoi Tessella- tions (SCVT). In this paper we present a detailed description of this new implementation and a comparison with the TriSphere algorithm.VII Workshop Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI