discusses stereoscopic 3D imaging based on line drawing of 3D shapes. We describe the major issues and challenges in generating stereoscopic 3D effects using lines only, with a couple of relatively simple approaches called each-eye-based and centereye-based. Each of these methods has its shortcomings

Communication of spatiality in 2D visual arts has been a central topic around which artistic experimentation has flourished for centuries. The inherent limitation of “flatness ” governing most traditional visual media has proven to be fertile ground for the emergence of advanced pictorial

for quantitatively evaluating spatial perception in a functional, NPR, stereo, immersive environment. The methods described in this paper borrow from both the art and perceptual psychology communities and will provide NPR researchers with a methodology for conducting user studies to perceptually validate new

In this paper we describe a set of interactive tools that we have built as an extension to our image-based stereo-scopic non-photorealistic rendering system. The base system is capable of automatically turning stereoscopic input images to stereoscopic pictures that resemble artwork, including

We introduce a novel computational model for objectively assessing the visual comfort of stereoscopic 3D imagery. Our model integrates research in visual perception with tools from stereo computer vision to quantify the degree of stereo coherence between both stereo half-images. We show

, and (2) providing controllability of the scene depth. The method offers patch-based solutions to a wide variety of stereoscopic image editing problems, including depth-guided texture synthesis, stereoscopic NPR, paint by depth, content adaptation, and 2D to 3D conversion. Several challenging cases

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

We present an algorithm for generating automatically stereoscopic paintings with varying levels of detail. We describe our interactive system built around the algorithm to enable users to adjust the level of detail of the painting. In this context of interactivity we have modified our stereo

on the key protein controlling nyctinasty are presented. The article also discusses the isolation of the “memory ” substance from the Venus flytrap and presents a mechanism for this action. 1

, and (2) providing controllability of the scene depth. The method offers patch-based solutions to a wide variety of stereoscopic image editing problems, including depth-guided texture synthesis, stereoscopic NPR, paint by depth, content adaptation, and 2D to 3D conversion. Several challenging cases