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Towards Event-based Animation

Towards Event-based Animation. By David Oziem Department of Computer Science. Many thanks to Colin Dalton, David Gibson and Neill Campbell. Introduction. Introduction. “A cheap costing for a photorealistic animated film is around £30,000 per minute”. Problem. Repeated actions.

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Towards Event-based Animation

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  1. Towards Event-based Animation By David Oziem Department of Computer Science Many thanks to Colin Dalton, David Gibson and Neill Campbell

  2. Introduction SRCFE 2003: David Oziem, Dept. Computer Science

  3. Introduction “A cheap costing for a photorealistic animated film is around £30,000 per minute” SRCFE 2003: David Oziem, Dept. Computer Science

  4. Problem • Repeated actions. • The standard approach would be to repeat a single action many times. • Boring, • Unnatural, • Easily noticed. • Animating a long sequence would be hugely expensive and time consuming. SRCFE 2003: David Oziem, Dept. Computer Science

  5. Auto-Regressive Process • Method of modelling sequences. • Learns patterns within a sequence, allowing new sequences to be generated. • Two potential media types: • Pixel values (Video clip) • Joint rotations (Animated character) SRCFE 2003: David Oziem, Dept. Computer Science

  6. Campfire • Example of a video texture. Eigenpath & Original clip SRCFE 2003: David Oziem, Dept. Computer Science

  7. Generated Sequences Plots of the motion through the eigenspace SRCFE 2003: David Oziem, Dept. Computer Science

  8. Generated Video Clip Original Clip Generated Sequence SRCFE 2003: David Oziem, Dept. Computer Science

  9. Barman SRCFE 2003: David Oziem, Dept. Computer Science

  10. Barman • The barman. • Very short clip, only 200 frames, • Does not loop fluently. SRCFE 2003: David Oziem, Dept. Computer Science

  11. Generated barman Generated version of the barman scene SRCFE 2003: David Oziem, Dept. Computer Science

  12. Horse Gait (States) • Not all motion continually repeats itself in a Gaussian distribution, • Transitions between states may occur. SRCFE 2003: David Oziem, Dept. Computer Science

  13. Crowd Scene (Event-driven) • State changes are driven by events. A KLT (Kanade-Lucas-Tomasi) feature tracker was used to find the average vertical velocity in each of these 16 blocks. SRCFE 2003: David Oziem, Dept. Computer Science

  14. Crowd scene (Sequence) The first 3 modes against time SRCFE 2003: David Oziem, Dept. Computer Science

  15. Crowd scene (Generation) • An ARP creates an array of motions which are • Completely unlinked, • Not event driven. SRCFE 2003: David Oziem, Dept. Computer Science

  16. Crowd scene (Generation) • The low frequency component used to dictate the general path of the primary mode. SRCFE 2003: David Oziem, Dept. Computer Science

  17. Generated crowd • Event occurs in all models at the same moment. • The crowd stands at different speeds and for varying durations. SRCFE 2003: David Oziem, Dept. Computer Science

  18. Future work • Other forms of ARP’s. Including; • ARX Auto-Regression with eXternal signal. • TAR Transition Auto-Regression. • Use of Hidden Markov Models to drive state changes. SRCFE 2003: David Oziem, Dept. Computer Science

  19. Summary • There are massive potential savings of generating sequences. • Natural motion is does NOT repeat perfectly. • Event driven state changes are difficult to model but it is possible. • ARP’s can generate new clips given that there is no change of state. SRCFE 2003: David Oziem, Dept. Computer Science

  20. Questions? • oziem@cs.bris.ac.uk • http://www.cs.bris.ac.uk/home/oziem/ SRCFE 2003: David Oziem, Dept. Computer Science

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