1 / 132

Animating (human) motion

Presented by: Yoram Atir Simon Adar. Animating (human) motion. Applications of computer animation. Movies Advertising Games Simulators …. General goals of the work presented. New methods aimed to save time/money/skills needed. - Study motion (texture). Agenda. - Basic concepts

marshall
Télécharger la présentation

Animating (human) motion

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Presented by: Yoram Atir Simon Adar Animating (human) motion

  2. Applications of computer animation • Movies • Advertising • Games • Simulators • …

  3. General goals of the work presented • New methods aimed to save time/money/skills needed. - Study motion (texture).

  4. Agenda - Basic concepts - Motion Synthesis/texture using motion capture • Physics/Biomechanics Motion Synthesis - Cartoon Motion Retargeting.

  5. Basic concepts • Animation world (3D) • Skeletal model representation • Model positioning • Keyframes • Motion capture • Frequency bands • Correlations Basic Concepts

  6. 3D animation world • (Human) model is animated in Object space • Animated model projected into “global” space • Camera is placed and rotated • Perspective is set • Other… Basic Concepts

  7. Skeletal representation • Each model has its own Default Pose • DOF’s – joint angles/translations relative to Default Pose • Hierarchical (tree) skeletal representation of model Picture from Lecture in Computer Graphics course Department of computer science University of Washington Basic Concepts

  8. Creating motion • Skeletal variations between frames • Overall rotation/Translation between frames • Correlate. General Problem: A LOT of work due to the large number of DOFS & high frame rate Basic Concepts

  9. Figure positioning • Forward kinematics (simplified): Figure positioning by joint data specification. Problem: • Tedious trial and error. Basic Concepts

  10. Figure positioning Inverse kinematics (simplified) • Joint data is acquired by solving for the final position • In general, This is an optimization problem with a large system of variables and constraints • Problems often are expressed as minimization problems, and solved using standard algorithms (gradient decent etc). • Usually, infinite number of possible solutions. • A “good” solution has to be more than “feasible” • Often one is obtained by embedding specific knowledge as additional constraints, and/or • Using Inverse kinematics as a part of a specific solution. Basic Concepts

  11. Basic methods for saving labor Motion capture KeyFrames Basic Concepts

  12. Keyframes • Specifying only part of DOFs and frames • Computer interpolation between them Problem: “smooth” interpolation looks unreal There are methods to apply “specific noise” • Term has historical roots Basic Concepts

  13. Motion capture • Acquired from “live action” • Copied onto animated character • Problem: Hard to adapt. • “Motion Editing” – methods to adapt mocap • Done in studios • Mocap libraries exist Basic Concepts

  14. Keyframing vs. Mocap Advantages Disadvantages • Control Keyframing Mocap Basic Concepts

  15. Keyframing vs. Mocap Advantages Disadvantages • Control • Intuitive Keyframing Mocap Basic Concepts

  16. Keyframing vs. Mocap Advantages Disadvantages • Control • Intuitive • Detail hard Keyframing Mocap Basic Concepts

  17. Keyframing vs. Mocap Advantages Disadvantages • Control • Intuitive • Detail hard • Many DOF Keyframing Mocap Basic Concepts

  18. Keyframing vs. Mocap Advantages Disadvantages • Control • Intuitive • Detail hard • Many DOF Keyframing • Detail easy Mocap Basic Concepts

  19. Keyframing vs. Mocap Advantages Disadvantages • Control • Intuitive • Detail hard • Many DOF Keyframing • Detail easy • All DOF Mocap Basic Concepts

  20. Keyframing vs. Mocap Advantages Disadvantages • Control • Intuitive • Detail hard • Many DOF Keyframing • Detail easy • All DOF • No control Mocap Basic Concepts

  21. Keyframing vs. Mocap Advantages Disadvantages • Control • Intuitive • Detail hard • Many DOF Keyframing • Detail easy • All DOF • No control • Not intuitive Mocap Basic Concepts

  22. Keyframe Data vs. Motion Capture Data

  23. Frequency Bands Right flat Right toe Left flat Left toe Basic Concepts

  24. Frequency Bands • Simplifies the form of the data • Low frequency Variations: Large scale motions. • Higher frequency variations: individual “noise” / Jitter Both are important to preserve in order to capture the essence of motion Basic Concepts

  25. Correlations • Joints angle/translation data is related to each other • Joint angles are correlated over time • Correlation “plot” is • (somewhat) Specific to the type of motion • Carries “personality” information (style) Basic Concepts

  26. More information… INTRODUCTION TO COMPUTER ANIMATION – Rick parent http://www.cis.ohio-state.edu/~parent/book/outline.html Splines http://www.people.nnov.ru/fractal/splines/Intro.html Hash Inc - Animation software (Movies, tutorials…) http://www.hash.com Google…

  27. Agenda - Basic concepts - Motion Synthesis/texture using motion capture • Physics/Biomechanics Motion Synthesis - Cartoon Motion Retargeting

  28. Goal: Motion Capture Assisted Animation • Create a method that allows an artist low-level control of the motion • Combine the strengths of keyframe animation with those of mocap Motion Capture Assisted Animation – Pullen/Bregler

  29. Goal: Motion Capture Assisted Animation “Sketch” an animation by keyframing • Animate only a few degrees of freedom • Set few keyframes “Enhance” the result with mocap data • Synthesize missing degrees of freedom • Texture keyframed degrees of freedom Motion Capture Assisted Animation – Pullen/Bregler

  30. What is a Motion Texture? • Every individual’s movement is unique • Synthetic motion should capture the texture • To “texture” means to add style to a pre-existing motion • Technically, texturing is a special case of synthesis

  31. Goal: Motion Capture Assisted Animation Blue = Keyframed Purple = Textured/Synthesized Motion Capture Assisted Animation – Pullen/Bregler

  32. How an Animator Works • A few degrees of freedom at first • Not in detail • Fill in detail with more keyframes later Motion Capture Assisted Animation – Pullen/Bregler

  33. The Method in Words • Choose degrees of freedom to drive the animation • Compare these degrees of freedom from the keyframed data to mocap • Find similar regions • Look at what the rest of the body is doing in those regions • Put that data onto the keyframed animation Motion Capture Assisted Animation – Pullen/Bregler

  34. Choices the Animator Must Make • Which DOF to use as matching angles • Which DOF to texture, which to synthesize • Which frequency band to use in matching • How many frequency bands to use in texturing • How many matches to keep • How many best paths to keep Motion Capture Assisted Animation – Pullen/Bregler

  35. Before Beginning:Choose Matching Angles Root x trans Root y trans Root z trans Root x rot Root y rot Root z rot Spine1 x Spine1 y Spine1 z Spine2 x Spine2 y Spine2 z Spine3 x Spine3 y Spine3 z Neck x Neck y Neck z Head x Head y Head z Head Aim x Head Aim y Head Aim z Left Clavicle x Left Clavicle y Left Clavicle z Left Shoulder x Left Shoulder y Left Shoulder z Left Elbow x Left Elbow y Left Elbow z Left Wrist x Left Wrist y Left Wrist z Right Clavicle x Right Clavicle y Right Clavicle z Right Shoulder x Right Shoulder y Right Shoulder z Right Elbow x Right Elbow y Right Elbow z Right Wrist x Right Wrist y Right Wrist z Left Hip x Left Hip y Left Hip z Left Knee x Left Knee y Left Knee z Left Ankle x Left Ankle y Left Ankle z Left Ball x Left Ball y Left Ball z Right Hip x Right Hip y Right Hip z Right Knee x Right Knee y Right Knee z Right Ankle x Right Ankle y Right Ankle z Right Ball x Right Ball y Right Ball z Time Time Time

  36. Matching Angles Drive the Synthesis Root x trans Root y trans Root z trans Root x rot Root y rot Root z rot Spine1 x Spine1 y Spine1 z Spine2 x Spine2 y Spine2 z Spine3 x Spine3 y Spine3 z Neck x Neck y Neck z Head x Head y Head z Head Aim x Head Aim y Head Aim z Left Clavicle x Left Clavicle y Left Clavicle z Left Shoulder x Left Shoulder y Left Shoulder z Left Elbow x Left Elbow y Left Elbow z Left Wrist x Left Wrist y Left Wrist z Right Clavicle x Right Clavicle y Right Clavicle z Right Shoulder x Right Shoulder y Right Shoulder z Right Elbow x Right Elbow y Right Elbow z Right Wrist x Right Wrist y Right Wrist z Left Hip x Left Hip y Left Hip z Left Knee x Left Knee y Left Knee z Left Ankle x Left Ankle y Left Ankle z Left Ball x Left Ball y Left Ball z Right Hip x Right Hip y Right Hip z Right Knee x Right Knee y Right Knee z Right Ankle x Right Ankle y Right Ankle z Right Ball x Right Ball y Right Ball z Time Time Time

  37. Motion Capture Data Root x trans Root y trans Root z trans Root x rot Root y rot Root z rot Spine1 x Spine1 y Spine1 z Spine2 x Spine2 y Spine2 z Spine3 x Spine3 y Spine3 z Neck x Neck y Neck z Head x Head y Head z Head Aim x Head Aim y Head Aim z Left Clavicle x Left Clavicle y Left Clavicle z Left Shoulder x Left Shoulder y Left Shoulder z Left Elbow x Left Elbow y Left Elbow z Left Wrist x Left Wrist y Left Wrist z Right Clavicle x Right Clavicle y Right Clavicle z Right Shoulder x Right Shoulder y Right Shoulder z Right Elbow x Right Elbow y Right Elbow z Right Wrist x Right Wrist y Right Wrist z Left Hip x Left Hip y Left Hip z Left Knee x Left Knee y Left Knee z Left Ankle x Left Ankle y Left Ankle z Left Ball x Left Ball y Left Ball z Right Hip x Right Hip y Right Hip z Right Knee x Right Knee y Right Knee z Right Ankle x Right Ankle y Right Ankle z Right Ball x Right Ball y Right Ball z Time Time Time

  38. Overview Steps in texture/synthesis method • Frequency analysis • Matching • Path finding • Joining Motion Capture Assisted Animation – Pullen/Bregler

  39. Example In the following series of slides: Hip angle = matching angle Spine angle = angle being synthesized Motion Capture Assisted Animation – Pullen/Bregler

  40. Frequency Analysis:Break into Bands Motion Capture Assisted Animation – Pullen/Bregler

  41. Frequency Analysis Band-pass decomposition of matching angles Keyframed Data Motion Capture Data Frequency Time Motion Capture Assisted Animation – Pullen/Bregler

  42. Frequency Analysis Chosen low frequency band Keyframed Data Motion Capture Data Frequency Time Motion Capture Assisted Animation – Pullen/Bregler

  43. Chosen Low Frequency Band Hip angle data (a matching angle) Keyframed Data Motion Capture Data Motion Capture Assisted Animation – Pullen/Bregler

  44. Making Fragments Break where first derivative changes sign Keyframed Data Motion Capture Data Motion Capture Assisted Animation – Pullen/Bregler

  45. Making Fragments Step through fragments one by one Keyframed Data Motion Capture Data Motion Capture Assisted Animation – Pullen/Bregler

  46. Matching Keyframed Fragment Motion Capture Assisted Animation – Pullen/Bregler

  47. Matching Motion Capture Data Keyframed Fragment Motion Capture Assisted Animation – Pullen/Bregler

  48. Matching Motion Capture Data Keyframed Fragment Motion Capture Assisted Animation – Pullen/Bregler

  49. Matching Compare to all motion capture fragments Angle in degrees Keyframed Mocap Time

  50. Matching Resample mocap fragments to be same length Angle in degrees Keyframed Mocap Time

More Related