1. Basic Theory of Motion Capture By: Vincent Verner

2. Overview  What is Motion Capture  How it is used  Three main types of motion capture methods  Technical terms  Hardware and human aspect of each method  Practical applications

3. What is Motion Capture Technology and What is it Used For?  Motion capture is the process of recording the movement of objects or people. It is used in military, entertainment, sports, and medical applications, and for validation of computer vision and robotics.  Motion capture has two basic applications  Recording  Real-time  Three basic methods for traditional motion capture  Magnetic  Optical  Mechanical

5. Magnetic Motion Capture  Magnetic motion capture systems utilize sensors placed on the body to measure the low-frequency magnetic field generated by a transmitter source.  Low production cost  Meant for body motion capture, not facial motion capture  Why?  Multiple Actors in close proximity  6-11 or more body sensors are typically used per person for accurate recordings

6. Body Suit

7. Receiver

8. Issues With Magnetic Motion Capture  Sensitivity to metal  Limited range  Slippage of markers  Encumbrance  Low effective sampling rate  Latency  Proximity based distortion with multiple actors

9. Optical Motion Capture  Two Main Methods  Passive(non-illuminated markers)  Active(LED)  Passive Markers (Reflective Markers)  Typically relies on camera  Active Markers (LED)  Typically relies on illuminated markers  Amount of cameras required  Only 1-2 needed or facial motion capture  8-16 or more required for accurate full-body motion capture  Most applicable method to 3d simulations  Variety in captured subject

11. Suit

12. Issues With Optical Motion Capture (Active)  Typically the most expensive option out of the three methods  Requires much more space compared to the other methods  More energy is consumed

13. Issues With Optical Motion Capture (Passive)  More issues with data corruption  Requires more time to capture data  Overall post processing time is increased

14. Electro-Mechanical Motion Capture  Rigid structures that use gyroscopic bearings in combination with potentiometers at the joint to directly determine body joint angles.  No need for special cameras  Use wireless systems to record movement  Perfect for real-time motion capture scenarios  Not affected by metal objects  Very cost efficient

15. Body Suit

16. Issues with Mechanical Motion Capture  Can be cumbersome with large battery back attached to spinal ridge  Somewhat Limited range of motion  Not suitable for gymnastic type movements

17. Basic Steps For Post Processing 1.Checking to make sure markers are in correct position 2.Marker Labeling Using Inverse Kinematics 3.Creating a skeleton from “T” pose 4.Checking for marker swaps and gaps

18. Initial Marker Position

19. Marker Labeling

20. Skeleton

21. How Can Motion Capture Technology be Implemented in Other Ways?

22. Simple Security Video Camera Motion Capture Algorithm (Created by Andrew Kirillov) // create filters Difference differenceFilter = new Difference( ); IFilter thresholdFilter = new Threshold( 15 ); // set backgroud frame as an overlay for difference filter differenceFilter.OverlayImage = backgroundFrame; // apply the filters Bitmap tmp1 = differenceFilter.Apply( currentFrame ); Bitmap tmp2 = thresholdFilter.Apply( tmp1 );

23. Removing Noisy Imaging IFilter erosionFilter = new Erosion( ); Bitmap tmp3 = erosionFilter.Apply( tmp2 );

24. Example of Noisy Pixilation

25. Highlighting Regions of Motion // extract red channel from the original image IFilter extrachChannel = new ExtractChannel( RGB.R ); Bitmap redChannel = extrachChannel.Apply( image ); //merge red channel with motion regions Merge mergeFilter = new Merge( ); mergeFilter.OverlayImage = tmp3; Bitmap tmp4 = mergeFilter.Apply( redChannel ); //replace red channel in the original image ReplaceChannel replaceChannel = new ReplaceChannel( RGB.R ); replaceChannel.ChannelImage = tmp4; Bitmap tmp5 = replaceChannel.Apply( image );

26. ARPool

27. What Have We Covered?  What Motion Capture is  How it is used  Three main types of motion capture methods  Technical terms relating to Motion Capture mothods  Hardware and human aspect of each method  Practical applications

28. References  O'Brien, J., Bodenheimer, R., Brostow, G., & Hodgins, J. (2000). Automatic joint parameter estimation from magnetic motion capture data. Graphics Interface, 53-60. Retrieved from http://graphics.berkeley.edu/papers/Obrien- AJP-2000-05/Obrien-AJP-2000-05.pdf  Kirillov, A. (2007, 03 27). Motion detection algorithms. Retrieved from http://www.codeproject.com/Articles/10248/Motion- Detection-Algorithms  Mocap resources. (2009, 04 16). Retrieved from http://www.metamotion.com/motion-capture/motion- capture.htm  Roesler, R. (2011, 03 29). A guide to optical motion capture. Retrieved from http://physbam.stanford.edu/cs448x/old/Optical_Motion_Ca pture_Guide.html