Interactive sketching of urban procedural models

International audience3D modeling remains a notoriously difficult task for novices despite significant research effort to provide intuitive and automated systems. We tackle this problem by combining the strengths of two popular domains: sketch-based modeling and procedural modeling. On the one hand, sketch-based modeling exploits our ability to draw but requires detailed, unambiguous drawings to achieve complex models. On the other hand, procedural modeling automates the creation of precise and detailed geometry but requires the tedious definition and parameterization of procedural models. Our system uses a collection of simple procedural grammars, called snippets, as building blocks to turn sketches into realistic 3D models. We use a machine learning approach to solve the inverse problem of finding the procedural model that best explains a user sketch. We use non-photorealistic rendering to generate artificial data for training con-volutional neural networks capable of quickly recognizing the procedural rule intended by a sketch and estimating its parameters. We integrate our algorithm in a coarse-to-fine urban modeling system that allows users to create rich buildings by successively sketching the building mass, roof, facades, windows, and ornaments. A user study shows that by using our approach non-expert users can generate complex buildings in just a few minutes

DeepSketch2Face: A Deep Learning Based Sketching System for 3D Face and Caricature Modeling

Face modeling has been paid much attention in the field of visual computing. There exist many scenarios, including cartoon characters, avatars for social media, 3D face caricatures as well as face-related art and design, where low-cost interactive face modeling is a popular approach especially among amateur users. In this paper, we propose a deep learning based sketching system for 3D face and caricature modeling. This system has a labor-efficient sketching interface, that allows the user to draw freehand imprecise yet expressive 2D lines representing the contours of facial features. A novel CNN based deep regression network is designed for inferring 3D face models from 2D sketches. Our network fuses both CNN and shape based features of the input sketch, and has two independent branches of fully connected layers generating independent subsets of coefficients for a bilinear face representation. Our system also supports gesture based interactions for users to further manipulate initial face models. Both user studies and numerical results indicate that our sketching system can help users create face models quickly and effectively. A significantly expanded face database with diverse identities, expressions and levels of exaggeration is constructed to promote further research and evaluation of face modeling techniques.Comment: 12 pages, 16 figures, to appear in SIGGRAPH 201

GIS and urban design

Although urban planning has used computer models and information systems sincethe 1950s and architectural practice has recently restructured to the use of computeraideddesign (CAD) and computer drafting software, urban design has hardly beentouched by the digital world. This is about to change as very fine scale spatial datarelevant to such design becomes routinely available, as 2dimensional GIS(geographic information systems) become linked to 3dimensional CAD packages,and as other kinds of photorealistic media are increasingly being fused with thesesoftware. In this chapter, we present the role of GIS in urban design, outlining whatcurrent desktop software is capable of and showing how various new techniques canbe developed which make such software highly suitable as basis for urban design.We first outline the nature of urban design and then present ideas about how varioussoftware might form a tool kit to aid its process. We then look in turn at: utilisingstandard mapping capabilities within GIS relevant to urban design; buildingfunctional extensions to GIS which measure local scale accessibility; providingsketch planning capability in GIS and linking 2-d to 3-d visualisations using low costnet-enabled CAD browsers. We finally conclude with some speculations on thefuture of GIS for urban design across networks whereby a wide range of participantsmight engage in the design process digitally but remotely