Londra

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Facial animation

Facial animation

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Londra Londra Presentation Transcript

  • Andres Adolfo Navarro NewballProf. Geoff Wyvill, Dr. Brendan McCane (University of Otago) Dr. Edmond Prakash (Manchester Metropolitan University)
  •  Several human facial animation models developed in the last 30 years. Less attention given to animal facial models. Animal facial anatomical features are usually humanised, oversimplified, cartoonised or ignored.
  •  We aim to create a virtual dog head capable of displaying facial expressions.
  • The expressive dog Londra
  •  Successfully synthesises dog facial expressions such as anger, affection, attention, fear, happiness, y awning and smelling without displaying anthropomorphic features. A preliminary validation suggests that most expressions were recognised consistently.
  •  A pure bottom up form of the layered approach for the bone, muscle, complementary, skin and fur layers. Tabulated Sphere Subsets to provide a fast way to approximate collisions between objects with constrained motion.
  •  Anatomical differences between humans and dogs. Lack of anatomical and biometric information. Scarcity of 3D digitised data from dogs.
  •  Charles Darwin Dog video observation Artificial pets Validation: ◦ Quantitative ◦ Qualitative ◦ Performance ◦ Beyond Darwin, C. (1890). The Expression of the Emotions in Man and Animals. London: Francis Darwin ed.
  • 11 Dog videos analysed which complement Darwin’s descriptionsSmell Open nostril Close nostril T 0 1,237 2,272 3,505 4,686 5,8
  • Attention Raise ears Twist head right Untwist head T 0 0,771 6,563 7,129 7,791 8,465
  • Anger Darwin’s angerMouthLipsEarsTongue T 0 1,488 1,7 2,028 2,574 3,064 27,048
  • 3.217Anger 2.277 1.7 0.885 0.846 0.788 0.767 0.754 0.7440.757 0.694 0.496 0.453 0.331 0.299 0.283 0.229 0.19 0.221 0.174 0.1730.199 0.091 0.076 0.076 0.094
  • AU Name AU Name 1 Upper lip raiser 13 Eyeball retractor 2 Lower lip depressor 14 Eyeball vertical mover – rotator 3 Nostril dilator 15 Head raiser 4 Mouth corner mover 16 Head lateral mover 5 Lower eyelid depressor 17 Head rotator 6 Upper eyelid depressor 18 Tail raiser 7 Ear advancer 19 Tail extender 8 Ear lowerer 20 Tail lateral mover 9 Jaw raiser 21 Body raiserAnger: 10 Tongue retractor, drawer 22 Left paw raiserTail is erect and rigid 18 (1) + 11 Tongue depressor 23 Right paw raiserEars are directed forward 7 (1) + 12 Eyeball mover - rotator 24 Hair raiserUpper lip is raised 1 (1) + 4 (0.5)
  • Setting up Processing Output DFACS Deformed skin AU 1 2 Name Upper lip raiser Lower lip depressor AU 13 14 Name Eyeball retractor Eyeball vertical mover – rotator Deformed tongue Deformed nose 3 Nostril dilator 15 Head raiser 4 Mouth corner mover 16 Head lateral mover 5 Lower eyelid 17 Head rotator 6 depressor 18 Tail raiser 7 Upper eyelid 19 Tail extender depressor 8 20 Tail lateral mover Ear advancer 9 21 Body raiser 10 Ear lowerer 22 Left paw raiser 11 Jaw raiser 23 Right paw raiser Tongue retractor, 12 24 Hair raiser drawer Tongue depressor Eyeball mover - rotator Import skull Transformed eyes Smoothed skin with lips Import nosePlace deformers Render animated expression Create tongue Place eyesPlace muscles F DFACS TSSs for: Euler AU Name AU Name -Jaw motion integration 1 2 3 Upper lip raiser Lower lip depressor Nostril dilator 13 14 15 Eyeball retractor Eyeball vertical mover – rotator Head raiser -Muscle and skin Render with 4 Mouth corner mover 16 Head lateral mover 5 Lower eyelid 17 Head rotator 6 depressor 18 Tail raiser 7 Upper eyelid 19 Tail extender Render with Blender 8 depressor 20 Tail lateral mover Ear advancer 9 21 Body raiser Ear lowerer 10 22 Left paw raiser interaction 11 Jaw raiser 23 Right paw raiser 12 Tongue retractor, 24 Hair raiser drawer Tongue depressor Eyeball mover - rotator OpengGL -Tongue motion
  • Frontalis Levator Oculis Temporalis Orbicularis Oculis Auricularis dorsales Levator Auricularis rostrales Zygomaticus Digastricus Masseter Mentalis Orbicularis OrisBarr, A. H. (1981). Superquadrics and Angle-Preserving Transformations. IEEE Comput.Graph. Appl., 1 (1), 11–23.
  • A) B) C) DistEyes α X ≤ X0 Sclera X ≥ X0 Pupil D Sn (X0, Y0, Z0) Z Iris Cornea P 1 DistEyes sinD) E) 2D MTM Groove MT Back Middle Tip
  • A) B) C) D1 D0D) R +d E) D2 D0 α R Axis
  • King, S. A. (2001). A facial model and animation techniques for animated speech. Ph. D. thesis, The Ohio State University. P P R R P’ P’ F F NmMuller, M., Heidelberger, B., Teschner, M., and Gross, M. (2005). Meshless deformationsbased on shape matching. In SIGGRAPH ’05: ACM SIGGRAPH 2005 Papers,New York, NY, USA, 471–478. ACM. D R FKobbelt, L. (2000). √3-subdivision. In SIGGRAPH ’00: Proceedings of the 27th annualconference on Computer graphics and interactive techniques, New York, NY, USA,103–112. ACM Press/Addison-Wesley Publishing Co. Ns
  • a b a b a b b a b a b Ma Ms Msc Msc Mss Mss s Msc= Colliding spheres subset. Mss= Minimal subset.Line of motion, 1 DOF n=3 n=3Ms= Approximation with m=3 m=7spheres. n X m = 9 tests n X m = 21 testsn = number of spheres in a TSSAB = Msa X Msb = compares=9 non redundant spheres of them = number of spheres in b same colour against spheres of the= 18 same colour only.n X m = 9 X 18 = 162 tests TTSS = 3 tests
  •  22 tests time step
  • WANG W., WANG J., KIM M.-S.: An algebraic conditionfor the separation of two ellipsoids. Comput. Aided Geom.Des. 18, 6 (2001), 531–539.
  •  The use of a more freely moving object. A flexible object interacting with more than one object The use of an object which has been divided in several sections which need to interact with each other. Extraordinary cases where some collisions need to be ignored.
  • A)  2 – 5 tests α 4 α α 2 α 4 β β 4 βB) β 2 C) 4
  • AU -14: Relax eyesAU -9: Lower head AU9: Raise head AU7: Open mandible AU16: Lick AU12: Left eyes AU13: Raise eyes AU6: Raise ears AU11: Twist head AU9: Raise head
  • A) Londra’s videos can be downloaded at: http://cic.javerianacali.edu.co/~anavarro/Londra/ OriginalB)C) Anger Attention Affection II YawnD) Happiness Fear Affection I Smell
  • Two frames U flow V flow Mixed flowA)A)B)C)
  • FPS25 21.3 20.820 18.5 19.2 18.2 17.9 17.215 14.7 13.2 13.710 FPS, SL25 FPS, SL10 Collision 60 145 245 370 1051 tests
  •  We followed a new pure bottom up approach which starts with a skull and does not require a pre-existing facial mesh. We introduced TSSs, a fast and appropriate method for constrained object interaction. We validated eight of Londra’s expressions successfully.
  •  Enhancing our bottom up approach by creating an anatomically accurate skull reshaping method in conjunction with zoology. Then, automating muscle placement. Our TSSs open a full field of research for constrained object interaction. For example, mirrored TSSs. The Londra model could be expanded to other real or non real non human creatures. And some of the techniques could be used in human systems.
  • • Blender 1• Blender 2• Blender 3