1. SS5305 – Advanced Motion Capture 1

2. Objectives Facial Capture Performance Capture Hardware Trends Software Trends Conclusions 2

3. Facial Capture Frederick I. Parke, University of Utah Computer Generated Animation of Faces 1972

4. 1988 B. Robertson, Mike the Talking Head, Computer Graphics World 11 (7):57 Facial Capture Method 1 – Phonemes When a particular type of sound is spoken: phonemes Specific shapes of the whole face are captured. (top down) Phonemes – the sounds that make up a word, not letters balloonb – ah – l – oo – n Method 2 – Feature Tracking Parts of the face are tracked separately. Each part contributes to overall motion. (bottom up) Motion is the sum of many features. Works for speech and other facial expressions

5. Trend – Markerless Facial Capture http://www.youtube.com/watch?v=UYgLFt5wfP4&feature=player_embedded Emily, Image Metrics, 2010 Surface is tracked based on image distortion rather than markers.

6. Problem: Motion capture records the body over volumes up to: 10 x 10 sq. meters (30 sq. ft) Facial capture records subtle details over space of: 30 x 30 cm (1 sq. ft) How to capture both the large-scale motion of the body and subtle motion of the face during a single performance?

7. Avater (2010), James Cameron Solution: Block off the face using individual, head-mounted cameras, which record only the face. Use motion cameras and passive markers for the body. Allows for both large volumes and small details. Trend – Performance capture is a collection of techniques that combine to record the total motion of an actor.

8. Markers include: Body captureGreen lines, white dots Facial captureHead-mounted device, /w camera booms Hair captureBlue and red ropes

9. Hardware Trends

10. Trend – Markerless capture: Origins in 3D laser scanning 3D Lego Digitizer http://www.rchoetzlein.com/project/digitizer/

11. Trend – Markerless capture: Structured Light Faster: Do all lines at once Projector with structured light mapped onto the object. Use two cameras to determine object structure. Structured light can be linear, binary coded, gray coded, or color coded. The encoding allows you to uniquely identify points. Light may be infrared (Kinetic). Q: High frequency gives details about height of point. But how do we tell if the point is on left or right side of obj? A: Low frequency gives overall characteristics of pixels.

12. No markers. Structured light creates a point cloud. Skeleton is fit inside point cloud from root joints to extremities. Torso defines primary orientation, and also constraints placement of next joint layer in hierarchy. Volume construction Point cloud Fit torse Fit extremities

13. Trend – Markerless capture: Direct-to-3D models http://www.youtube.com/watch?v=dTisU4dibSc&playnext=1&l ist=PLD31C3C36D294EEDB Christian Theobalt, Stanford University http://www.stanford.edu/group/biomotion/Markerless.html Performance Capture from Sparse Multi-view Video, SIGGRAPH 2010

14. Trend – Monocular capture Fabio Remondino, Andreas Roditakis Institute for Geodesy and Photogrammetry - ETH Zurich, Switzerland 3D Reconstruction of Human Skeleton from Single Images or Monocular Video Sequences 2003, 25th Pattern Recognition Symposium One camera, without depth, is under-constrained. However, the human body has fixed limb lengths and ratios. Use the body ratios as an additional constraint.

15. Trend – Low Cost Systems Cheap hardware: Microsoft Kinect, Web cameras. Open source software: OpenKinectopen kinect drivers libfreenectopen kinect drivers OpenNIskeleton fitting FaceAPIfacial tracking Main challenges: 1) Integration into existing frameworks, 2) Usually requires programming experience 3) Can be difficult to modify for research

16. Software Trends

17. Motion Graph: A database of motion capture clips, connected to one another to represent transitions between actions. Motion graphs can be represented by a finite state machine, a set of states with edges representing state transitions. StandRun Jump Motion Graphs

18. Planning and Directing Motion Capture For Games Melianthe Kines, Gamasutra. January 19, 2000 http://www.gamasutra.com/view/feature/3420/planning_and_directing_motion_.php http://www.gamasutra.com/view/feature/3420/planning_and_directing_motion_.php Trend – Motion Graphs in Gaming

19. What are the advantages and disadvantages of motion graphs for gaming? Advantages 1. Fast. Motion is simply played back from pre-recorded data. 2. Interactive. Motion can be changed immediately by transitioning to a different state. 3. Modular. Different motions can easily be swapped in. 4. Extensible. More states can be added to the graph. Disadvantages 1. Jump transitions between capture clips 2. Motion may not match scene exactly. e.g. jump over chasm 3. Cannot grasp objects accurately. No inverse kinematics. 4. Cannot move in any direction 5. Interruptions from outside forces not easily handled

20. Trend – Motion Blending in Gaming Michael Gleicher, Hyun Joon Shin, Lucas Kovar, Andrew Jepsen Snap-Together Motion: Assembling Run-Time Animations Interactive 3D Graphics 2003 “In order to create streams of high-quality motion, current applications [games] assemble static clips of motion created with traditional animation techniques such as motion capture or keyframing. The assembly process requires making transitions between motions. These transitions may be difficult to create, such as a transition between a running clip and one where the character is lying down, or trivial, if the end of one clip is identical to the beginning of the next. In practice, simple techniques such as linear blends are capable of creating transitions in cases where the motions are similar.”

21. Common solutions in Gaming: 1. Jump transitions Linear blending between motion clips 2. Motion may not matchBlend with scene constraints scene exactly (extend jump over river) 3. Cannot grasp objectsAdd inverse kinematics to arms in game characters. 4. Cannot move in anyAdd steering. directionSimple: re-orient, then play walk cycle Advanced: add IK to legs 5. Interruptions fromUse a rag-doll physics switch. outside forces When object hits.. Turn on physics, apply force.

22. Trend – Motion Graphs How would you instruct a character to follow an arbitrary path using a set of pre-recorded captured motion? Lucas Kovar, Michael Gleicher, Frederic Pighin. Motion Graphs, SIGGRAPH 2002.

23. Trend – Motion Graphs Alla Safonova Jessica K. Hodgins, Carnegie-Melon University. Construction and optimal search of interpolated motion graphs SIGGRAPH 2007 How do we make energy optimal motion based on several, arbitrary constraints? Uses motion capture data, but in arbitrary, non-acted scenarios.

24. Overview Motion capture Point clouds Skeleton fitting Facial capture Performance capture Marker data Re-targeting 3D model capture Motion graphs (e.g Gaming) Blending Optimization Sequencing Animation Post processing (cleaning) Skinning Secondary motion Physical capture / Haptics Joint data Monoccular video INPUTOUTPUT

25. Conclusion Facial Recognition is critical in real world applications; cyber security, safety, etc Performance trends lead to Virtual Reality Markerless is good, it might not be reference standard. Software shall be more and more embedded than programmer oriented, more towards to end user familiar.

26. CASE STUDIES

27. Gary Sanderson: the biomechanics of a Sprinter Gary is an 18 year old sprinter the only difference is that he has Cerebral Palsy and wants to run at the next Olympics The Problem: Gary was fitted with an ankle foot orthosis (or splint) to help support the ankle. But Gary’s foot was regularly collapsing as the foot was loaded during running causing great strain around the foot and ankle. Copyright of Professor Jim Richards, University of Central Lancashire

28. Motion analysis showed the degree to which the ankle was collapsing Copyright of Professor Jim Richards, University of Central Lancashire

29. Re-think Based on the information a redesign of the ankle foot orthosis (or splint) was conducted. The focus of this change was to provide greater stability about ankle joint. This in turn should help performance !?! Copyright of Professor Jim Richards, University of Central Lancashire

30. The new orthosis shows no collapsing although the foot is still internally rotated Before After Copyright of Professor Jim Richards, University of Central Lancashire

31. Do we get an improvement of performance about the ankle? The ankle is more stable This should allow a better platform from which to push off This should lead to a significant increase in the power production Copyright of Professor Jim Richards, University of Central Lancashire

32. Do we get an improvement of performance about the ankle? Shortly after the fitting of the new orthosis Gary recorded his fastest ever time for the 100 m, 13.8 seconds, 1.5 seconds off his previous best time! Copyright of Professor Jim Richards, University of Central Lancashire

33. Entertainment Applications Films Television Computer and video games

34. Animation Facial Caption

35. Movie/Television Seamless and believable visual effects Films – “Titanic“ – "Gladiator“ – "The Mummy Returns", – "Star Wars Episode 1 - the Phantom Menace” Crowd Scenes Stunt Work Photorealistic foreground characters