Adding Depth to Cartoons Using Sparse Depth (In)equalities

This paper presents a novel interactive approach for adding depth information into hand-drawn cartoon images and animations. In comparison to previous depth assignment techniques our solution requires minimal user effort and enables creation of consistent pop-ups in a matter of seconds. Inspired by perceptual studies we formulate a custom tailored optimization framework that tries to mimic the way that a human reconstructs depth information from a single image. Its key advantage is that it completely avoids inputs requiring knowledge of absolute depth and instead uses a set of sparse depth (in)equalities that are much easier to specify. Since these constraints lead to a solution based on quadratic programming that is time consuming to evaluate we propose a simple approximative algorithm yielding similar results with much lower computational overhead. We demonstrate its usefulness in the context of a cartoon animation production pipeline including applications such as enhancement, regi...

• Type: Conference
• Year: 2010
• Where: EUROGRAPHICS
• Authors: Daniel Sýkora, David Sedlacek, Sun Jinchao, John Dingliana, Steven Collins
• Keywords: Computer Graphics, Computer Vision, EUROGRAPHICS 2010, Reconstructs Depth Information, Sparse Depth