Motion Capture, Motion Edition - Inria
Motion Capture,Motion Editionlionel.reveret@inria.fr2011
Motion Capture,Motion Edition Overview– Historical background– Motion capture systems– Motion capture workflow– Re-use of motion data– Combining motion data and physical modelingMotion Capture, Motion Edition lionel.reveret@inria.fr2
Motion Capture,Motion Edition Overview– Historical background– Motion capture systems– Motion capture workflow– Re-use of motion data– Combining motion data and physical modelingMotion Capture, Motion Edition lionel.reveret@inria.fr3
Historical background Photography– Studying motion Rotoscoping– Key-framing appearance Puppetry– Disappearing animatorMotion Capture, Motion Edition lionel.reveret@inria.fr4
Historical background Photography of motion– E. Muybridge, 1830-1904 Photograph Study for horse racing zoopraxiscope– E.-J. Marey, 1830-1904 Physiologist, Collège de France “méthode graphique” (1859) Chronophotography (1882)Motion Capture, Motion Edition lionel.reveret@inria.fr5
Historical Background E.-J. Marey– “méthode graphique”, 1859Motion Capture, Motion Edition lionel.reveret@inria.fr6
Historical background Rotoscoping– Key-framing appearance[Disney, 1937][Fleischer, 1915]Motion Capture, Motion Edition lionel.reveret@inria.fr7
Historical background Puppetry– J. Henson, the Muppet Show, 80s Remote control from capture of thepuppeteer’s gesture– Tippet Studio, Jurassic Park,1992 Inverse robotics, electrical engine creates motionsignalMotion Capture, Motion Edition lionel.reveret@inria.fr8
Motion Capture,Motion Edition Overview– Historical background– Motion capture systems– Motion capture workflow– Re-use of motion data– Combining motion data and physical modelingMotion Capture, Motion Edition lionel.reveret@inria.fr9
Motion capture systems Mechanical– Exo-skeleton Electromagnetic– 6 DOF of a solid Optical– 3D positions of markers Embedded device– Gyroscope, accelerometerMotion Capture, Motion Edition lionel.reveret@inria.fr10
Motion capture systems Mechanical, exoskeleton : very reliable, low cost: constrained motion AnimazooMotion Capture, Motion Edition lionel.reveret@inria.fr11
Motion capture systems Electromagnetic, : 6 DOF few markers: sensitive to interference, limited spaceMotion Capture, Motion Edition lionel.reveret@inria.fr12
Motion capture system Optical, active markersEx: each marker encoded by LED pulse : no ambiguities between markers: several markers for rigid body, limitednumber of markers[PhaseSpace]Motion Capture, Motion Edition lionel.reveret@inria.fr13
Motion capture systems Optical, passive markers– reflective marker, directional lighting : no limits in markers: loss of markersMotion Capture, Motion Edition lionel.reveret@inria.fr14
Motion capture systems Embedded device (gyroscope,accelerometer ) : as small as 5 mm3 , wireless: signals difficult to calibrate[Moven / xsens]Motion Capture, Motion Edition lionel.reveret@inria.fr[Nintendo]15
Motion capture beyond markers Structured-light scanner Silhouette and convex hull[Zhang et al., 04][Carranza et al., 03]Motion Capture, Motion Edition lionel.reveret@inria.fr16
Motion Capture,Motion Edition Overview– Historical background– Motion capture systems– Motion capture workflow– Re-use of motion data– Combining motion data and physical modelingMotion Capture, Motion Edition lionel.reveret@inria.fr17
Motion capture workflow Data sampled 100Hz Goal :– 3D rotations for 3D skeleton body pose– 3D positions for facial animation Post-processing– filtering, marker loss, etcMotion Capture, Motion Edition lionel.reveret@inria.fr18
Motion capture workflow Rotational measure– direct mapping– morphological adaptation can be complex see motion retargetting From 3D positions to 3D rotations:– 3 points enough for 6 degrees of freedom of rigidbody (bone)– physiological constraints less DOF less markersMotion Capture, Motion Edition lionel.reveret@inria.fr19
Motion capture workflow Rotational measure– direct mapping motion curve– morphological adaptation can be complex From 3D positions to 3D rotations:– 3 points enough for 6 degrees of freedom ofrigid body (bone)– physiological constraints less DOF less markersMotion Capture, Motion Edition lionel.reveret@inria.fr20
Motion capture workflow Open problems in R&D(Optical passive markers)– identifying markers– occlusion/crossing markers– losing/recovering markers– appropriate filteringMotion Capture, Motion Edition lionel.reveret@inria.fr21
Motion Capture,Motion Edition Overview– Historical background– Motion capture systems– Motion capture workflow– Re-use of motion data– Combining motion data and physical modelingMotion Capture, Motion Edition lionel.reveret@inria.fr22
Re-use of motion data motion clip limited to the capture session target character might be in anunexpected position (video games) need for modifying data withoutdestroying naturalness of motionMotion Capture, Motion Edition lionel.reveret@inria.fr23
Re-use of motion Motion warping– modifying animation curvesWarp:Time warp :Curve warp:1.2.3.4.C(t) C’(t’)t g(t’)C’(t) a(t)C(t) b(t)Choose key-frameEdit pose C’(ti) at key-frameSolve for a(ti) or b(ti)Interpolate a(t) and b(t)[Popovic and Witkin, 95]Motion Capture, Motion Edition lionel.reveret@inria.fr24
Re-use of motion Motion retargetting– Smoothly enforce hard constrains (not just IK) Footplants, distances, etc– Optimize minimal displacement curve givenconstrains– Original mocap data as starting point[Gleicher, 98]Motion Capture, Motion Edition lionel.reveret@inria.fr25
Re-use of motion Starting in 2002, methods based onmassive database of mocap data Great initiative from CMU– http://mocap.cs.cmu.edu– 2605 motion clips, 23 categories, severalsubjects– free for research– amc (rotations) and c3d (markers) formatsMotion Capture, Motion Edition lionel.reveret@inria.fr26
Motion re-use Motion graph– transition/blend between segments of motion– metric between two frames on joints global positions time window for smoothnessmotion 2– graph path optimized w.r.t.touserhintstmotion 1tMotion Capture, Motion Edition lionel.reveret@inria.fr[Kovar et al., 02]27
Motion re-use Motion graph as dynamic programming– cost function to satisfy user constrains– choose best clips sequence[Arikan et al., 03][Treuille et al., 07]Motion Capture, Motion Edition lionel.reveret@inria.fr28
Motion re-use Statistical methods– reduction of character parametric space (setof joint orientations) to high-level parameters– inference in parametric space given userconstrains using optimizationmost probable pose w.r.t. constrains, [Grochow et al., 2004]Motion Capture, Motion Edition lionel.reveret@inria.fr29
Motion re-use Facial animation– Transfer of local motion of individual markers– Transfer of global motionMotion Capture, Motion Edition lionel.reveret@inria.fr30
Motion re-use Facial animation– Transfer of local motion of markers direct animation of the target 3D modelcomplex morphological adaptation[Noh and Neuman, 01]Motion Capture, Motion Edition lionel.reveret@inria.fr31
Motion re-use Facial animation– Transfer of global motion mapping independent of morphologyuser must specify several target shapes[Reveret et Essa, 01][Pyun et al., 03]Motion Capture, Motion Edition lionel.reveret@inria.fr32
Motion Capture,Motion Edition Overview– Historical background– Motion capture systems– Motion capture workflow– Re-use of motion data– Combining motion data and physical modelingMotion Capture, Motion Edition lionel.reveret@inria.fr33
Motion capture and physics Mapping optical markers to physics– physical model of character (angular spring)– 3D markers attached to virtual springs– physical model acts as a “realistic” filter[Zordan and Van der Horst, 03][Kry and Reveret, 07]Motion Capture, Motion Edition lionel.reveret@inria.fr34
Motion capture and physics Space-time constrains [Witkin and Kass, 88]– physical simulation lacks of control– re-write physics laws as an optimization Given a particule with propulsion fmd2x/dt2 – f – mg 0 Find fi so that boundaries constrains are satisfied and use asless fuel as possiblefi arg min Σ fi2with: m(xi 1 – 2xi xi-1)/h2 – fi –mg 0and x1 a, and xn bMotion Capture, Motion Edition lionel.reveret@inria.fr35
Motion capture and physics Spacetime constrains using mocap– Key-frame taken as pose constrains– Estimate torques on a simplified phys model– Edit motion by changing physical parameter[Popovic and Witkin, 99]Motion Capture, Motion Edition lionel.reveret@inria.fr36
Motion capture and physics Spacetime constrains using mocap– Estimate all physical parameters[Liu et al., 04]Motion Capture, Motion Edition lionel.reveret@inria.fr37
Motion capture,Motion edition ��––"Motion Warping,“, Zoran Popovic, Andy Witkin in Computer Graphics (SIGGRAPH) 1995.Michael Gleicher. “Retargetting Motion to New Characters”, Proceedings of SIGGRAPH 98. In Computer Graphics AnnualConferance Series. 1998.Lucas Kovar Michael Gleicher Frederic Pighin. Motion Graphs. ACM Transactions on Graphics 21(3) (Proceedings ofSIGGRAPH 2002). July 2002.Treuille, A. Lee, Y. Popović, Z. , “Near-optimal Character Animation with Continuous Control”, ACM Transactions on Graphics26(3) (SIGGRAPH 2007)Okan Arikan, David A. Forsyth, James O'Brien. Motion Synthesis from Annotations. ACM Transactions on Graphics (ACMSIGGRAPH 2003), Vol: 33, No: 3, pp 402--408, 2003.M. Brand, A. Hertzmann, “Style Machine”, SIGGRAPH 2000.Keith Grochow, Steven L. Martin, Aaron Hertzmann, Zoran Popović. Style-based Inverse Kinematics. ACM Transactions onGraphics (Proceedings of SIGGRAPH 2004), 2004.Li Zhang, Noah Snavely, Brian Curless, and Steven M. Seitz. Spacetime Faces: High-resolution capture for modeling andanimation. In ACM SIGGRAPH Proceedings, Los Angeles, CA, Aug., 2004.J. Carranza, C. Theobalt. M. Magnor, H.P. Seidel, Free-Viewpoint Video of Human Actors. in Proc. of ACM SIGGRAPH 2003, p.569-577, San Diego, CAJ.Y. Noh and U. Neumann, "Expression Cloning,“ Computer Graphics, Proceedings of ACM SIGGRAPH 2001, Los Angeles CA,August 2001, pages 277-288.Pyun, Kim, Chae, Kang, and Shin / An Example-Based Approach for Facial Expression Cloning, ACM/EG SCA, 2003.L. Reveret, I. Essa, Visual Coding and Tracking of Speech Related Facial Motion, IEEE CVPR International Workshop on Cues inCommunication, Hawai, USA, Decembre 9, 2001.Victor B. Zordan and Nicholas C. Van Der Horst, “Mapping optical motion capture data to skeletal motion using a physical model”,ACM/EG SCA, 2003.A. Witkin and M. Kass , “Spacetime constraints”, Computer Graphics (Proc. SIGGRAPH '88), Vol. 22, 1988, pp. 159-168.Zoran Popovic and Andy Witkin, "Physically Based Motion Transformation." in Computer Graphics (SIGGRAPH) 1999.Liu, C. K., Hertzmann, A. and Popović, Z. Learning Physics-based Motion Style with Nonlinear Inverse Optimization ( ACMSIGGRAPH 2005 )Motion Capture, Motion Edition lionel.reveret@inria.fr38
Motion Capture, Motion Edition - lionel.reveret@inria.fr 38 Motion capture, Motion edition References – "Motion Warping,“, Zoran Popovic, Andy Witkin in Com puter Graphics (SIGGRAPH) 1995. – Michael Gleicher. “Retargetting Motion to New Chara cters”, Proceedings of SIGGRAPH 98. In Computer Graphics Annual Conferance Series. 1998.
INRIA1, CEREA2, UVSQ3, FRANCE Etienne.Huot@inria.fr Giuseppe Papari Lithicon Norway AS NORWAY papari@lithicon.com Isabelle Herlin INRIA1, CEREA2 FRANCE Isabelle.Herlin@inria.fr Abstract This paper describes modeling and numerical computa-tion of orthogonal bases, which are used to describe im-ages and motion fields. Motion estimation from .
HowtoImplement Embedded Packet Capture Managing Packet DataCapture SUMMARYSTEPS 1. enable 2. monitor capture capture-name access-list access-list-name 3. monitor capture capture-name limit duration seconds 4. monitor capture capture-name interface interface-name both 5. monitor capture capture-name buffer circular size bytes .
Facebook: SAMSON Connect Email: stephane.redon@inria.fr Phone: 33 4 38 78 16 92 Address: NANO-D Antenne INRIA – GIANT MINATEC Parvis Louis Néel 38000 Grenoble France April, 10, 2017 Appointments 01/08- : INRIA: Research Scientist, head of the NANO-D group
2. monitor capture capture-name access-list access-list-name 3. monitor capture capture-name limit duration seconds 4. monitor capture capture-name interface interface-name both 5. monitor capture capture-name buffer circular size bytes EmbeddedPacketCaptureOverview 4 EmbeddedPacketCaptureOverview PacketDataCapture
Device# monitor capture mycap start *Aug 20 11:02:21.983: %BUFCAP-6-ENABLE: Capture Point mycap enabled.on Device# show monitor capture mycap parameter monitor capture mycap interface capwap 0 in monitor capture mycap interface capwap 0 out monitor capture mycap file location flash:mycap.pcap buffer-size 1 Device# Device# show monitor capture mycap
r1#no monitor capture buffer MYCAPTUREBUFFER Capture Buffer deleted r1#show monitor capture buffer MYCAPTUREBUFFER parameters Capture Buffer MYCAPTUREBUFFER does not exist r1#no monitor capture point ip cef INTERNALLAN fa0/1 *Jun 21 00:07:25.471: %BUFCAP-6-DELETE: Capture Point INTERNALLAN deleted. r1#show monitor capture point INTERNALLAN
Sample Capture Session switch1(config)#monitor session 3 type capture switch1(config-mon-capture)#buffer-size 65535 switch1(config-mon-capture)#source interface gi4/15 both switch1#sh monitor capture Capture instance [1] : Capture Session ID : 3 Session status : up rate-limit value : 10000 redirect index : 0x809 buffer-size : 2097152
Anatomy and physiology for microblading techniques Unit reference number: L/615/6166 Level: 4 Guided Learning (GL) hours: 20 Overview The aim of this unit is to provide learners with the necessary underpinning knowledge of relevant human anatomy and physiology to enable them to perform effective and safe microblading services for eyebrow treatments. Learners will develop an understanding of .
