Image-Based Stereoscopic Painterly Rendering

Abstract

We present a new image-based stereoscopic painterly algorithm that we use to automatically generate stereoscopic paintings. Our work is motivated by contemporary painters who have explored the aesthetic implications of painting stereo pairs of canvases. We base our method on two real images, acquired from spatially displaced cameras. We derive a depth map by utilizing computer vision depth-from-stereo techniques and use this information to plan and render stereo paintings. These paintings can be viewed stereoscopically, in which case the pictorial medium is perceptually extended by the viewer to better suggest the sense of distance.