Rotoscoping on Stereoscopic Images and Videos

Abstract

Creating an animation based on video footage (rotoscoping) often requires significant manual work. For monoscopic videos diverse publications already feature (semi-)automatic techniques to apply non-photorealistic image abstraction (NPR) to videos. This paper addresses abstraction of 3D stereo content minimizing stereoscopic discomfort in images and videos. We introduce a completely autonomous framework that enhances stereo and temporal consistency. Stereoscopic coherence with consistent textures for both eyes is produced by warping the left and right images into a central disparity domain followed by mapping them back to the left and right view. Smooth movements with reduced flickering are achieved by considering optical flow in the propagation of abstract features between frames. The results show significant improvements of stereo consistency without discomforting artifacts in the depth perception. We extend existing stroke based rendering (SBR) for higher accuracy at strong image gradients. Furthermore, we demonstrate that our stereo framework is easily applicable to other point-based abstraction styles. Finally, we evaluate the stereo consistency of our results in a small user study and show that the comfort of the visual appearance is maintained.