Virtual Painting
Vince Scheib (left) and Bill Baxter using dAb virtual painting system
J. Carlyle Sitterson Hall
Wednesday, 7:00 to 9:00 p.m.
Free and open to the public
Principal Investigator:
Ming C. Lin, Beverly W. Long Distinguished Professor, Computer Science, UNC
Co-Investigator:
Dinesh Manocha, Phi Delta Theta/Matthew Mason Distinguished Professor, Computer Science, UNC
Project Team:
Bill Baxter, Microsoft Research
Vincent Scheib, Google Inc.
Jeremy Wendt, UNC Computer Science Graduate Student
Project Description:
Recent advances in computer graphics have made progress with reproducing the look of painting. This project explores the benefits of recreating the "sight, touch, action and feeling" of the artistic process itself.
The system, dAb, provides the user with the traditional tools of a painter. This setting, conceptually equivalent to a real world painting environment, allows anyone to control a virtual brush as he or she would a real brush.
To achieve this, we have designed a physically-based, deformable, 3-D brush model and bi-directional, two-layer, paint model. These allow the user to produce complex brush strokes intuitively. The haptic feedback enhances the sense of realism and provides tactile cues that enable the user to better manipulate the paintbrush.
We model the brush head as a subdivision surface mesh wrapped around a spring-mass particle system skeleton. The particle system reproduces the basic motion and behavior of a brush head, while the deformable mesh skinned around this skeleton represents the actual shape of the head.
Complementing our expressive brushes, we present a paint model capable of capturing complex effects interactively. Our paint model incorporates variable wetness and opacity, conservation of volume, and a hardware-accelerated bi-directional paint transfer algorithm. It supports the following operations and techniques expected from acrylic or oil painting: blending, bi-directional transfer, complex brush loading, variable dryness, glazing, and impasto.
Wednesday, 7:00 to 9:00 p.m.
Free and open to the public
Principal Investigator:
Ming C. Lin, Beverly W. Long Distinguished Professor, Computer Science, UNC
Co-Investigator:
Dinesh Manocha, Phi Delta Theta/Matthew Mason Distinguished Professor, Computer Science, UNC
Project Team:
Bill Baxter, Microsoft Research
Vincent Scheib, Google Inc.
Jeremy Wendt, UNC Computer Science Graduate Student
Project Description:
Recent advances in computer graphics have made progress with reproducing the look of painting. This project explores the benefits of recreating the "sight, touch, action and feeling" of the artistic process itself.
The system, dAb, provides the user with the traditional tools of a painter. This setting, conceptually equivalent to a real world painting environment, allows anyone to control a virtual brush as he or she would a real brush.
To achieve this, we have designed a physically-based, deformable, 3-D brush model and bi-directional, two-layer, paint model. These allow the user to produce complex brush strokes intuitively. The haptic feedback enhances the sense of realism and provides tactile cues that enable the user to better manipulate the paintbrush.
We model the brush head as a subdivision surface mesh wrapped around a spring-mass particle system skeleton. The particle system reproduces the basic motion and behavior of a brush head, while the deformable mesh skinned around this skeleton represents the actual shape of the head.
Complementing our expressive brushes, we present a paint model capable of capturing complex effects interactively. Our paint model incorporates variable wetness and opacity, conservation of volume, and a hardware-accelerated bi-directional paint transfer algorithm. It supports the following operations and techniques expected from acrylic or oil painting: blending, bi-directional transfer, complex brush loading, variable dryness, glazing, and impasto.
