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Gesichtsanimation für Video- konferenzanwendungen VisionIC

Gesichtsanimation für Video- konferenzanwendungen VisionIC. Jürgen Rurainsky, Dr. Peter Eisert Bildsignalverarbeitung Heinrich-Hertz-Institut, Berlin 08/08/14. Outline. VisionIC Advanced Videophone Communication model (phase 1) Face Feature Detection Communication model (phase 2)

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Gesichtsanimation für Video- konferenzanwendungen VisionIC

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  1. Gesichtsanimation für Video-konferenzanwendungenVisionIC Jürgen Rurainsky, Dr. Peter Eisert BildsignalverarbeitungHeinrich-Hertz-Institut, Berlin 08/08/14 J. Rurainsky – Heinrich-Hertz-Institute

  2. Outline • VisionIC • Advanced Videophone • Communication model (phase 1) • Face Feature Detection • Communication model (phase 2) • Head modeling • Model-based Video Coding • Analysis by Synthesis • Application • Animation J. Rurainsky – Heinrich-Hertz-Institute

  3. VisionIC • Entwicklung einer intelligenten Vision-Plattform samt Pilotanwendungen für den Massenmarkt • Parallel-Prozessor Architektur, CMOS-Kamera mit integrierter Merkmalskaskade (pulskodierte neuronale Netze) • Anwendungen: • Advanced Videophone (HHI) • Dialogmodem • Kfz-Vollerfassung J. Rurainsky – Heinrich-Hertz-Institute

  4. Advanced Videophone • Kommunikationstreffpunkt in einer virtuellen Umgebung • Videotelefondienst mit Merkmalen einer immersiven Telekonferenz • Portable und stationäre Endgeräte (PDA, Laptop, Multi-Kamera-System) • 3D-Bildverarbeitungstechnologien (Analyse, Synthese, 3D-Modellierung, MPEG-4 Codierung) • Kopf-Schulter-Ansichten animiert mit Facial Animation Parameters (FAP) • Ziel: Kommunikation mit nur einigen kbit/s (Video) J. Rurainsky – Heinrich-Hertz-Institute

  5. 3D-Head modeling t Input Synthesis Transport FAP analysis Output Communication model (phase 1) Face Feature Detection J. Rurainsky – Heinrich-Hertz-Institute

  6. Face Feature Detection (eye) • Face color segmentation • Face geometry • Binary iris template matching • Iris diameter calculated from face geometry (rough assumption) • Deformable iris mapping • Deformable eye lid mapping with anchor point • Eye geometry calculated from face geometry (assumption) J. Rurainsky – Heinrich-Hertz-Institute

  7. Face Feature Detection (mouth) • Face geometry • Binary mouth template matching • Search region extraction related to face geometry • Bézier curve fitting • Bézier curve fitting with a deformable curve (5 control points) • Intensity • Extreme values J. Rurainsky – Heinrich-Hertz-Institute

  8. t Input Face Feature Detection Synthesis Transport FAP analysis Output Communication model (phase 2) Face Feature Tracking 3D-Head modeling J. Rurainsky – Heinrich-Hertz-Institute

  9. Head modeling Source: Jörgen Ahlberg (Linköping University) J. Rurainsky – Heinrich-Hertz-Institute

  10. Model-based Video Coding J. Rurainsky – Heinrich-Hertz-Institute

  11. ( ) I FAP , , FAP , model K - 0 N 1 Analysis by Synthesis • Exploits all pixels in the image • Minimization of the image differences in an analysis-synthesis loop model frame camera frame difference J. Rurainsky – Heinrich-Hertz-Institute

  12. Applications • Low bit-rate video coding(UMTS, mobile applications, avatars) • Virtual Conferencing(VisionIC, BMBF project) J. Rurainsky – Heinrich-Hertz-Institute

  13. Facial Animation original sequence synthesized sequence bit-rate: < 1 kbit/s J. Rurainsky – Heinrich-Hertz-Institute

  14. Animation of different People J. Rurainsky – Heinrich-Hertz-Institute

  15. Danke J. Rurainsky – Heinrich-Hertz-Institute

  16. Example J. Rurainsky – Heinrich-Hertz-Institute

  17. Face Feature Detection (chin line) J. Rurainsky – Heinrich-Hertz-Institute

  18. J. Rurainsky – Heinrich-Hertz-Institute

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