Importance-Driven Composition of Multiple Rendering Styles

We introduce a non-uniform composition that integrates multiple rendering styles in a picture driven by an importance map. This map, either issued from saliency estimation or designed by a user, is introduced both in the creation of the multiple styles and in the final composition. Our approach accommodates a variety of stylization techniques, such as color desaturation, line drawing, blurring, edge-preserving smoothing and enhancement. We illustrate the versatility of the proposed approach and the variety of rendering styles on different applications such as images, videos, 3D scenes and even mixed reality. We also demonstrate that such an approach may help in directing user attention.

[1]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[2]  Jens Schneider,et al.  ClearView: An Interactive Context Preserving Hotspot Visualization Technique , 2006, IEEE Transactions on Visualization and Computer Graphics.

[3]  Seungyong Lee,et al.  Multi-scale line drawings from 3D meshes , 2006, I3D '06.

[4]  Xavier Granier,et al.  On-line visualization of underground structures using context features , 2010, VRST '10.

[5]  Hyung W. Kang,et al.  A unified scheme for adaptive stroke-based rendering , 2006, The Visual Computer.

[6]  Frédo Durand,et al.  Learning to predict where humans look , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[7]  Nanning Zheng,et al.  Learning to Detect a Salient Object , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Nanning Zheng,et al.  Learning to Detect A Salient Object , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Seungyong Lee,et al.  Shape‐simplifying Image Abstraction , 2008, Comput. Graph. Forum.

[10]  Mateu Sbert,et al.  Importance-Driven Focus of Attention , 2006, IEEE Transactions on Visualization and Computer Graphics.

[11]  Adam Finkelstein,et al.  Directing gaze in 3D models with stylized focus , 2006, EGSR '06.

[12]  Bruno Lévy,et al.  Geometry-aware direction field processing , 2009, TOGS.

[13]  Pascal Barla,et al.  Structure-preserving manipulation of photographs , 2007, NPAR '07.

[14]  Pascal Barla,et al.  X-toon: an extended toon shader , 2006, NPAR.

[15]  Douglas DeCarlo,et al.  Abstracted painterly renderings using eye-tracking data , 2002, NPAR '02.

[16]  Jürgen Döllner,et al.  Image and Video Abstraction by Anisotropic Kuwahara Filtering , 2009, Comput. Graph. Forum.

[17]  Seungyong Lee,et al.  Flow-Based Image Abstraction , 2009, IEEE Transactions on Visualization and Computer Graphics.

[18]  Douglas DeCarlo,et al.  Stylization and abstraction of photographs , 2002, ACM Trans. Graph..

[19]  Dieter Schmalstieg,et al.  Interactive Focus and Context Visualization for Augmented Reality , 2007, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.

[20]  Karol Myszkowski,et al.  3D unsharp masking for scene coherent enhancement , 2008, SIGGRAPH 2008.

[21]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[22]  Xiaogang Jin,et al.  Real-time saliency-aware video abstraction , 2009, The Visual Computer.

[23]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Wei Hua,et al.  Confidence-Based Color Modeling for Online Video Segmentation , 2009, ACCV.

[25]  Holger Winnemöller,et al.  Real-time video abstraction , 2006, SIGGRAPH 2006.

[26]  Jonathan D. Cohen,et al.  Level of Detail for 3D Graphics , 2012 .

[27]  Michael F. Cohen,et al.  GradientShop: A gradient-domain optimization framework for image and video filtering , 2010, TOGS.

[28]  Arindam Dey,et al.  An Augmented Reality X-Ray system based on visual saliency , 2010, 2010 IEEE International Symposium on Mixed and Augmented Reality.

[29]  Song-Chun Zhu,et al.  From image parsing to painterly rendering , 2009, TOGS.

[30]  J. Cohen,et al.  Color Science: Concepts and Methods, Quantitative Data and Formulas , 1968 .