Hasso-Plattner-Institut
  
Hasso-Plattner-Institut
Prof. Dr. Jürgen Döllner
  
 

Flow-based Image and Video Abstraction

This project investigates automatic non-photorealistic image processing techniques for the creation of simplified stylistic illustrations from color images, videos and 3D renderings based on the bilateral and difference of Gaussians filters.

Our method extends the approach of [Winnemöller et al. 2006] to use iterated bilateral filtering for abstraction and difference-of-Gaussians (DoG) for edge extraction by adapting it to the local orientation of the input. To represent local orientation we construct a smooth tensor field. From the eigenvectors of this tensor field we derive a vector field that has similar characteristics as the edge tangent flow (ETF) of [Kang et al. 2007], but its computation is much less expensive. Besides gradient calculation, only smoothing with a box or Gaussian filter is necessary. In contrast to that, ETF construction requires several iterations of a nonlinear filter with large filter kernel.

The xy-separated bilateral filter [Pham and van Vliet 2005] used by Winnemöller et al. suffers from horizontal and vertical artifacts. These artifacts appear in particular when the filter is applied iteratively. Our approach works by first filtering in direction of the gradient and then filtering the intermediate result in perpendicular direction. When applied iteratively our approach does not suffer from horizontal or vertical artifacts and creates smooth output at curved boundaries.

DoG edges often look frayed and don’t reassemble straight line and curve segments very well. To work around this limitation, [Kang et al. 2007] recently introduced the concept of flow-based difference-of-Gaussians which, compared to DoG edges, create more coherent lines. They replaced the DoG filter by a flow-guided anisotropic kernel whose shape is defined by the ETF. Comparable high-quality results can be achieved by a separated implementation with corresponding reduced computational complexity. We first apply a one-dimensional difference-of- Gaussian filter in direction of the gradient and then apply smoothing along the vector field that we derive from the smoothed structure tensor.

Publications

Winnemöller, Holger and Kyprianidis, Jan Eric and Olsen, Sven C.
Computers & Graphics, vol. 36(6):740-753 2012
Semmo, Amir and Kyprianidis, Jan Eric and Döllner, Jürgen
In Painho, Marco and Santos, Maribel Yasmina and Pundt, Hardy, ed., Geospatial Thinking, of Lecture Notes in Geoinformation and Cartography, pages 359-378. Springer, 5 2010
Döllner, Jürgen and Kyprianidis, Jan Eric
In Georg Gartner and Felix Ortag, ed., Cartography in Central and Eastern Europe, of Lecture Notes in Geoinformation and Cartography, pages 263–277, 2010 Springer.
Kyprianidis, Jan Eric and Döllner, Jürgen
In W. Engel, ed., ShaderX7 - Advanced Rendering Techniques, pages 285–302. Charles River Media, 2009
Döllner, Jürgen and Kyprianidis, Jan Eric
In Georg Gartner and Felix Ortag, ed., Proceedings of the First ICA Symposium for Central and Eastern Europe 2009, pages 371–385, 2009 Vienna University of Technology,
Kyprianidis, Jan Eric and Döllner, Jürgen
In Ik Soo Lim and Wen Tang, ed., EG UK Theory and Practice of Computer Graphics, pages 51–58, 6 2008 Eurographics Association.
Kyprianidis, Jan Eric and Döllner, Jürgen
2008

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