Preserving global features of fluid animation from a single image using video examples

We synthesize animations from a single image by transferring fluid motion of a video example globally. Given a target image of a fluid scene, an alpha matte is required to extract the fluid region. Our method needs to adjust a user-specified video example for producing the fluid motion suitable for the extracted fluid region. Employing the fluid video database, the flow field of the target image is obtained by warping the optical flow of a video frame that has a visually similar scene to the target image according to their scene correspondences, which assigns fluid orientation and speed automatically. Results show that our method is successful in preserving large fluid features in the synthesized animations. In comparison to existing approaches, it is both possible and useful to utilize our method to create flow animations with higher quality.

[1]  Ken-ichi Anjyo,et al.  Animating Pictures of Fluid using Video Examples , 2009, Comput. Graph. Forum.

[2]  William A. Barrett,et al.  Object-based image editing , 2002, ACM Trans. Graph..

[3]  Edward H. Adelson,et al.  Motion without movement , 1991, SIGGRAPH.

[4]  Adrien Treuille,et al.  Keyframe control of smoke simulations , 2003, ACM Trans. Graph..

[5]  Thomas Brox,et al.  High Accuracy Optical Flow Estimation Based on a Theory for Warping , 2004, ECCV.

[6]  Lance Williams,et al.  Animating images with drawings , 1994, SIGGRAPH.

[7]  Patrick Pérez,et al.  Dense Estimation of Fluid Flows , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Nicolas Courty,et al.  Crowd motion capture , 2007 .

[9]  Song-Chun Zhu,et al.  Modeling textured motion : particle, wave and sketch , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[10]  Jessica K. Hodgins,et al.  Flow-based video synthesis and editing , 2004, SIGGRAPH 2004.

[11]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[12]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[13]  David Salesin,et al.  Animating pictures with stochastic motion textures , 2005, ACM Trans. Graph..

[14]  Stefano Soatto,et al.  Dynamic Textures , 2003, International Journal of Computer Vision.

[15]  Ariel Shamir,et al.  Improved seam carving for video retargeting , 2008, SIGGRAPH 2008.

[16]  Tian Fang,et al.  High Resolution Animated Scenes from Stills , 2007, IEEE Trans. Vis. Comput. Graph..

[17]  Bobby Bodenheimer,et al.  Synthesis and evaluation of linear motion transitions , 2008, TOGS.

[18]  Meng Sun,et al.  Video input driven animation (VIDA) , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[19]  Dani Lischinski,et al.  A Closed-Form Solution to Natural Image Matting , 2008 .

[20]  Richard Szeliski,et al.  Video textures , 2000, SIGGRAPH.

[21]  Antonio Torralba,et al.  SIFT Flow: Dense Correspondence across Different Scenes , 2008, ECCV.

[22]  Irfan A. Essa,et al.  Image-based motion blur for stop motion animation , 2001, SIGGRAPH.

[23]  Irfan A. Essa,et al.  Graphcut textures: image and video synthesis using graph cuts , 2003, ACM Trans. Graph..

[24]  Ken Tsutsuguchi,et al.  Dynamic texture: physically based 2D animation , 1999, SIGGRAPH '99.

[25]  Takeo Igarashi,et al.  As-rigid-as-possible shape manipulation , 2005, ACM Trans. Graph..

[26]  Jitendra Malik,et al.  Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  Ken-ichi Anjyo,et al.  Creating Fluid Animation from a Single Image using Video Database , 2011, Comput. Graph. Forum.

[28]  Matthijs C. Dorst Distinctive Image Features from Scale-Invariant Keypoints , 2011 .