Making Face Presentation for computer graphics and vision XUYAN YAN
Motivation <ul><li>It is a super hot topic nowdays, in computer graphics industry ,that producing realistic, expressive an...
Making Faces Guenter, Grimm, Wood, Malvar, Pighin 1997 <ul><li>Aim :  Take video of an person, and generate a representati...
<ul><ul><li>Track correspondences between dots(camera to camera & frame to frame) to determine dot motion over time </li><...
A Morphable Model For The Synthesis Of 3D Faces Blanz , Vetter 1999 <ul><li>The technique derives a morphable face model b...
<ul><li>directly use the densely sampled geometry of the exemplar faces obtained by laser scanning of over 200 hundred per...
Synthesis of Faces Modeler Result Database Face Analyzer 3D Head Morphable Face Model
Matching a Morphable 3D-Face-Model <ul><li>This model represent the geometry of a face with a shape-vector S and  represen...
Automated Parameter Estimation <ul><ul><li>Ambient:  intensity, color  </li></ul></ul><ul><ul><li>Parallel:  intensity, co...
Example:
Examples
An interesting topic and What I will be working on in future:  -  exchange face in images... <ul><li>It is also based on t...
Exchange
Reference <ul><li>Brian Guenter, Cindy Grimm, Henrique Malvar, Daniel Wood,  Making Faces , SIGGRAPH 1998. </li></ul><ul><...
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Making Face

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Making Face

  1. 1. Making Face Presentation for computer graphics and vision XUYAN YAN
  2. 2. Motivation <ul><li>It is a super hot topic nowdays, in computer graphics industry ,that producing realistic, expressive animated faces. This technology has been used in creating believable virtual characters for moives and television.(e.g The Curious Case of Benjamin Button ) </li></ul><ul><li>I am quite interested in the topic of “making face” . As it seems so COOL and FUN!! </li></ul>
  3. 3. Making Faces Guenter, Grimm, Wood, Malvar, Pighin 1997 <ul><li>Aim : Take video of an person, and generate a representation that allows reconstruction from any view </li></ul><ul><li>Steps: </li></ul><ul><ul><li>Take video with 6 cameras of a person speaking with 182 colored dots glued all over their face </li></ul></ul>
  4. 4. <ul><ul><li>Track correspondences between dots(camera to camera & frame to frame) to determine dot motion over time </li></ul></ul><ul><ul><li>Generate a 3D model by scanning the head (with the dots) </li></ul></ul><ul><ul><li>For each frame, compute model vertex motion according to the (known) locations of the dots </li></ul></ul><ul><ul><li>Two stage fit: first determine motion for a grid of points, then determine vertex motion </li></ul></ul><ul><ul><li>To render, simply texture map the 3D fitted model </li></ul></ul><ul><ul><ul><li>Textures come from the video streams </li></ul></ul></ul><ul><ul><ul><li>Remove dots from the textures, and the resulting holes filled in </li></ul></ul></ul><ul><ul><ul><li>Blend textures into one view independent texture </li></ul></ul></ul>
  5. 5. A Morphable Model For The Synthesis Of 3D Faces Blanz , Vetter 1999 <ul><li>The technique derives a morphable face model by transforming the shape and texture of the examples into a vector space representation. New faces and expressions can be modeled by forming linear combinations of the prototypes. </li></ul>
  6. 6. <ul><li>directly use the densely sampled geometry of the exemplar faces obtained by laser scanning of over 200 hundred person’s head. </li></ul><ul><li>It built a morphable face model by automatically establishing correspondence between all of our 200 exemplar faces. </li></ul><ul><li>The goal of such an extended morphable face model is to represent any face as a linear combination of a limited basis set of face prototypes. </li></ul><ul><li>The interactive face modeling system enables human users to create new characters and to modify facial attributes by varying the model coefficients. </li></ul>
  7. 7. Synthesis of Faces Modeler Result Database Face Analyzer 3D Head Morphable Face Model
  8. 8. Matching a Morphable 3D-Face-Model <ul><li>This model represent the geometry of a face with a shape-vector S and represent the texture of a face by a texture-vector T </li></ul><ul><li>R = Rendering Function </li></ul><ul><li>p = Parameters for Pose, Illumination, ... </li></ul><ul><li>Find optimal a, b, r ! </li></ul>
  9. 9. Automated Parameter Estimation <ul><ul><li>Ambient: intensity, color </li></ul></ul><ul><ul><li>Parallel: intensity, color, direction </li></ul></ul><ul><ul><li>Color: contrast, gains, offsets </li></ul></ul><ul><ul><li>150 shape coefficients  i </li></ul></ul><ul><ul><li>150 texture coefficients  i </li></ul></ul><ul><ul><li>3D Geometry </li></ul></ul><ul><ul><li>head position </li></ul></ul><ul><ul><li>Head orientation </li></ul></ul><ul><ul><li>focal length </li></ul></ul>Face Parameters <ul><ul><li>Light and Color </li></ul></ul>
  10. 10. Example:
  11. 11. Examples
  12. 12. An interesting topic and What I will be working on in future: - exchange face in images... <ul><li>It is also based on the the Morphable Model, which captures the range of possible shapes. and textures observed in a dataset of 3D scans. </li></ul><ul><li>This system applys an algorithm that estimates a textured 3D face model from a single image, along with all relevant scene parameters, such as 3D orientation, position, focal length of the camera, and the direction and intensity of illumination . </li></ul><ul><li>Given a set of about 7 feature points that are manually defined by the user in an interactive interface, the algorithm automatically fits a Morphable Model of 3D faces to the image and optimizes all model parameters. </li></ul>
  13. 13. Exchange
  14. 14. Reference <ul><li>Brian Guenter, Cindy Grimm, Henrique Malvar, Daniel Wood, Making Faces , SIGGRAPH 1998. </li></ul><ul><li>V. Blanz, C. Basso, T. Poggio and T. Vetter, Reanimating Faces in Images and Video , EUROGRAPHICS 2003. </li></ul><ul><li>V. Blanz, K. Scherbaum, T. Vetter, H.P. Seidel, Exchanging Faces in Images , EUROGRAPHICS 2004. </li></ul>
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