Smart Scribbles for Sketch Segmentation


We present Smart Scribble, a new scribble-based interface for user-guided segmentation of digital sketchy drawings.

July 5, 2012
EU Computer Graphics Forum (EU CGF) 2012



Chino Noris (Disney Research/ETH Joint PhD)

Daniel Sykora (Czech Technical University in Prague)

Ariel Shamir (The Interdisciplinary Center, Herzelia, Israel)

Stelian Coros (Disney Research)

Brian Whited (Walt Disney Animation Studios)

Maryann Simmons (Walt Disney Animation Studios)

Alexander Sorkine-Hornung (Disney Research)

Markus Gross (Disney Research/ETH Zurich)

Robert W. Sumner (Disney Research)

Smart Scribbles for Sketch Segmentation


In contrast to previous approaches based on simple selection strategies, Smart Scribbles exploits richer geometric and temporal information, resulting in a more intuitive segmentation interface. We introduce a novel energy minimization formulation in which both geometric and temporal information from digital input devices is used to define stroke-to-stroke and scribble-to-stroke relationships. Although the minimization of this energy is, in general, a NP-hard problem, we use a simple heuristic that leads to a good approximation and permits an interactive system able to produce accurate labelings even for cluttered sketchy drawings. We demonstrate the power of our technique in several practical scenarios such as sketch editing, as-rigid-as-possible deformation and registration, and on-the-fly labeling based on pre-classified guidelines.

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