Innovations in Visualization

Evaluation of Non-Photorealistic Rendering (NPR) for Illustration

Tobias Isenberg
Sheelagh Carpendale
Mario Costa Sousa
Petra Neumann

Goal

In this project we are studying both traditional hand-drawn and computer-generated non-photorealistic line drawings. In particular, we are interested in those line drawings that are used for illustration, e.g., in scientific and medical applications. For example, we want to improve our understanding of the differences between the two ways line drawings are currently generated. We hope that the findings of this study will help the research community to improve the techniques used for creation of line drawing illustrations to better meet the needs of viewers and creators of illustrations. Also, we hope to determine the needs of professional illustrators in terms of their needs of computer tools to assist them in creating illustrations. Thus, the study will reveal further avenues of investigation as to the computer-assisted creation of line drawing illustrations.

Publications

Tobias Isenberg, Petra Neumann, Sheelagh Carpendale, Mario Costa Sousa and Joaquim A. Jorge. Non-Photorealistic Rendering in Context: An Observational Study. In Proceedings of the Fourth International Symposium on Non-Photorealistic Animation and Rendering (NPAR 2006, June 5–7, 2006, Annecy, France). ACM Press, pages 115-126, 2006. PDF Paper
Tobias Isenberg, Petra Neumann, Sheelagh Carpendale, Mario Costa Sousa and Joaquim A. Jorge. Aesthetics of Hand-Drawn and Computer-Generated Illustrations. In Bruce Gooch and László Neumann and Werner Purgathofer and Mateu Sbert Casasayas (Eds.) Dagstuhl Seminar 06221 on Computational Aesthetics in Graphics, Visualization and Imaging, 2006. PDF Paper
Tobias Isenberg, Petra Neumann, Sheelagh Carpendale, Mario Costa Sousa and Joaquim A. Jorge. Non-Photorealistic Rendering in Context: An Observational Study. Research report 2005-805-36, Department of Computer Science, University of Calgary, Canada, dec, 2005. PDF Paper

Links

Support

This work is partially supported by grants from Alberta Ingenuity, the Canadian Foundation for Innovation, and the University of Calgary.