Exploratory modeling with collaborative design spaces

Enabling ordinary people to create high-quality 3D models is a long-standing problem in computer graphics. In this work, we draw from the literature on design and human cognition to better understand the design processes of novice and casual modelers, whose goals and motivations are often distinct from those of professional artists. The result is a method for creating exploratory modeling tools, which are appropriate for casual users who may lack rigidly-specified goals or operational knowledge of modeling techniques. Our method is based on parametric design spaces, which are often high dimensional and contain wide quality variations. Our system estimates the distribution of good models in a space by tracking the modeling activity of a distributed community of users. These estimates drive intuitive modeling tools, creating a self-reinforcing system that becomes easier to use as more people participate. We present empirical evidence that the tools developed with our method allow rapid creation of complex, high-quality 3D models by users with no specialized modeling skills or experience. We report analyses of usage patterns garnered throughout the year-long deployment of one such tool, and demonstrate the generality of the method by applying it to several design spaces.

[1]  Christopher Leckie,et al.  An Evaluation of Criteria for Measuring the Quality of Clusters , 1999, IJCAI.

[2]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[3]  A. MacEachren,et al.  Visualization in Modern Cartography: Setting the Agenda , 1994 .

[4]  Laura A. Dabbish,et al.  Labeling images with a computer game , 2004, AAAI Spring Symposium: Knowledge Collection from Volunteer Contributors.

[5]  Frédo Durand,et al.  Image-driven navigation of analytical BRDF models , 2006, EGSR '06.

[6]  Abhishek Ranjan,et al.  A suggestive interface for image guided 3D sketching , 2004, CHI.

[7]  Philip H. S. Torr,et al.  VideoTrace: rapid interactive scene modelling from video , 2007, SIGGRAPH 2007.

[8]  Yoshua Bengio,et al.  Locally Weighted Full Covariance Gaussian Density Estimation , 2004 .

[9]  J. Hughes,et al.  SmoothSketch: 3D free-form shapes from complex sketches , 2006, ACM Trans. Graph..

[10]  Janet L. Kolodner,et al.  CASE-BASED CREATIVE DESIGN , 1993 .

[11]  D. Navinchandra Exploration and Innovation in Design: Towards a Computational Model , 1990 .

[12]  Willemien Visser,et al.  The Cognitive Artifacts of Designing , 2006 .

[13]  Frederic I. Parke,et al.  A parametric model for human faces. , 1974 .

[14]  Takeo Igarashi,et al.  A suggestive interface for 3D drawing , 2001, SIGGRAPH Courses.

[15]  Szymon Rusinkiewicz,et al.  Modeling by example , 2004, SIGGRAPH 2004.

[16]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[17]  Greg Miller,et al.  The Promise of Parallel Universes , 2007, Science.

[18]  Zoran Popovic,et al.  The space of human body shapes: reconstruction and parameterization from range scans , 2003, ACM Trans. Graph..

[19]  Tomás Feder,et al.  Optimal algorithms for approximate clustering , 1988, STOC '88.

[20]  Marc Alexa,et al.  FiberMesh: designing freeform surfaces with 3D curves , 2007, SIGGRAPH 2007.

[21]  D. Gatz,et al.  The standard error of a weighted mean concentration—I. Bootstrapping vs other methods , 1995 .

[22]  Jason Weber,et al.  Creation and rendering of realistic trees , 1995, SIGGRAPH.

[23]  Paul A. Beardsley,et al.  Design galleries: a general approach to setting parameters for computer graphics and animation , 1997, SIGGRAPH.

[24]  Stephan R. Sain,et al.  Multi-dimensional Density Estimation , 2004 .

[25]  Thomas Vetter,et al.  A morphable model for the synthesis of 3D faces , 1999, SIGGRAPH.

[26]  H. Van Dyke Parunak Book review: Exploration and Innovation in Design: Towards a Computational Model By D. Navinchandra (Springer Verlag, 1991) , 1992 .

[27]  David C. Brown,et al.  Design Problem Solving: Knowledge Structures and Control Strategies , 1989 .

[28]  John S. Gero,et al.  Design Prototypes: A Knowledge Representation Schema for Design , 1990, AI Mag..

[29]  Steven M. Seitz,et al.  Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..

[30]  Peter Shirley,et al.  An Anisotropic Phong BRDF Model , 2000, J. Graphics, GPU, & Game Tools.

[31]  E. Parzen On Estimation of a Probability Density Function and Mode , 1962 .

[32]  Wojciech Matusik,et al.  A data-driven reflectance model , 2003, ACM Trans. Graph..

[33]  Qi Su,et al.  Internet-scale collection of human-reviewed data , 2007, WWW '07.

[34]  Alexei A. Efros,et al.  Scene completion using millions of photographs , 2007, SIGGRAPH 2007.

[35]  Greg Linden,et al.  Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .

[36]  Bill Buxton,et al.  Sketching User Experiences: Getting the Design Right and the Right Design , 2007 .

[37]  Alexei A. Efros,et al.  Photo clip art , 2007, SIGGRAPH 2007.

[38]  K. Strimmer,et al.  Statistical Applications in Genetics and Molecular Biology A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics , 2011 .

[39]  Daniel Cohen-Or,et al.  Image Appearance Exploration by Model‐Based Navigation , 2009, Comput. Graph. Forum.

[40]  C. Robert Simulation of truncated normal variables , 2009, 0907.4010.

[41]  Paul P. Maglio,et al.  On Distinguishing Epistemic from Pragmatic Action , 1994, Cogn. Sci..

[42]  Lucas Kovar,et al.  Simplicial families of drawings , 2001, UIST '01.

[43]  Lisa Tweedie,et al.  Interactive Visualisation Artifacts: How can Abstractions Inform Design? , 1996, BCS HCI.