Warping of 2D Facial Images Using Image Interpolation by Triangle Subdivision

ABSTRACT Image warping is a technology to transform input images to be suitable for given conditions and has been recently utilized in changing face shape of characters in the field of movies or animation. Mesh warping which is one of warping methods that change shapes based on the features of face forms warping images by forming rectangular mesh groups around the eyes, nose, and mouth and matching them 1:1. This method has a problem in the resultant images are distorted in the segments of boundaries between meshes when there are errors in mesh control points or when meshes have been formed as many small area meshes. This study proposes a triangle based image interpolation technique to minimize the occurrence of errors in the process of forming natural warping images of face and process accurate results with a small amount of arithmetic operation and a short time. First, feature points that represent the face are found and these points are connected to form basic triangle meshes. The fact that the proposed method can reduce errors occurring in the process of warping while reducing the amount of arithmetic operation and time is shown through experiments. Keywords : Facial image warping(얼굴 영상 워핑), Feature-based method(특징기반 방법), Triangle subdivision(삼각형 반복분할), Image interpolation(영상보간법), Mesh warping(메쉬워핑)

[1]  George Wolberg,et al.  Skeleton-based image warping , 2005, The Visual Computer.

[2]  Timothy F. Cootes,et al.  Active Appearance Models , 1998, ECCV.

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

[4]  Luiz Velho,et al.  Warping and morphing of graphical objects , 1998 .

[5]  George Wolberg,et al.  Digital image warping , 1990 .

[6]  Nur Arad,et al.  Image Warping Using Few Anchor Points and Radial Functions , 1995, Comput. Graph. Forum.

[7]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[8]  Hyeong-Seok Ko,et al.  An Extended Modal Warping Approach to Real-Time Simulation of Thin Shells , 2007 .

[9]  Dalia Bonilla,et al.  Control Methods for Fluid-Based Image Warping , 2011 .

[10]  Carsten Rother,et al.  A stereo approach that handles the matting problem via image warping , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Jun Zhang,et al.  Sketching MLS Image Deformations On the GPU , 2008, Comput. Graph. Forum.

[12]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[13]  Hwang， Ki-Tae.  Morphing and Warping using Delaunay Triangulation in Android Platform , 2010 .

[14]  John Hart,et al.  Detail preserving shape deformation in image editing , 2007, SIGGRAPH 2007.

[15]  Jeongjin Lee,et al.  3D Cloud Animation using Cloud Modeling Method of 2D Meteorological Satellite Images , 2010 .

[16]  Scott Schaefer,et al.  Image deformation using moving least squares , 2006, ACM Trans. Graph..

[17]  In-So Kweon,et al.  Stabilizing Omnidirectional Videos Using 3D Structure and Spherical Image Warping , 2011, MVA.

[18]  Alvy Ray Smith,et al.  Planar 2-pass texture mapping and warping , 1987, SIGGRAPH.

[19]  Alan H. Barr,et al.  Global and local deformations of solid primitives , 1984, SIGGRAPH.

[20]  Luiz Velho,et al.  Sketch-based warping of RGBN images , 2011, Graph. Model..