Optical Motion Capture by ert554898

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									Optical Motion Capture

       Bobby Bruckart
         Ben Heipp
        James Martin
       Molly Shelestak
                 Outline
• History
  – Types of Motion Capture
  – Development of Motion Capture
• State-of-the-Art
  – Hardware / Software
  – Data Collection Algorithms
  – Pros & Cons
• Future
  – Possible solutions to current problems
  – Possible future paths
   Types of Motion Capture
• History              1. Mechanical Motion
   – Types of Motion
      Capture
                          Capture
   – Development of    2. Optical Motion Capture
      Motion Capture
• State-of-the Art
                       3. Electromagnetic
• Future                  (magnetic) Motion
                          Capture
   Mechanical Motion Capture
• performer wears a human-shaped set of straight metal pieces
• other types: gloves, mechanical arms, articulated models
• pro:
    – no interference from light or magnetic fields
• con:
    –   the technology has no awareness of ground
    –   equipment must be calibrated often.
    –   does not know which way the performer's body is pointing
    –   absolute positions are not known but are calculated from the rotations
            Optical Motion Capture
•   performer wears reflective dots that are followed by several cameras and the
    information is triangulated
•   markers are either reflective, or infra-red emitting
•   developed primarily for biomedical applications
•   pro:
     – performer feels free to move due to no cables connecting body to the
         equipment
     – larger volumes possible
     – more performers are possible
     – very clean, detailed data
•   con:
     – it is prone to light interference
     – occlusion
     – rotations of body parts must be solved for and are not absolute
     – performer must wear a suit with dots and balls
     – information has to be post-processed or 'tracked' before viewing
     – comparatively high cost
 Electromagnetic Motion Capture
• performer wears an array of magnetic receivers which track location
  with respect to a static magnetic transmitter
• First use: military
• often layered
• pro:
   – positions are absolute, rotations are measure absolutely
   – can be real-time
   – relatively cheaper than optical
• con:
   – magnetic distortion
   – data prone to noise and interference
   – performers wear cables connecting them to a computer
   – relatively low sampling speed
              Development
• History
   – Types of Motion
      Capture
   – Development of
      Motion Capture
• State-of-the Art
• Future
 Early 1980s – Beginning of optical
              systems

• MIT Architecture Machine Group & New
  York Institute of Technology Computer
  Graphics Lab experimented with optical
  tracking of the human body
• few cameras and markers with limited
  success.
• created virtual stick-figure marionette
1985-1988 Jim Henson Productions

• ability to control the position
  and mouth movements of a low
  resolution character in real-time

• Waldo C. Graphic
        1988: deGraf/Wahrman
        “Mike the Talking Head”


• shows off the real-time
  capabilities

• driven by a specially built
  controller

• The Silicon Graphics hardware
  provided real-time interpolation
  between facial expressions and
  head geometry as controlled by
         1989 Kleiser-Walczak
• Dozo
• used optically-based solution
  from Motion Analysis
  (multiple cameras to
  triangulate the images of small
  pieces of reflective tape placed
  on the body)
• resulting output is the 3-D
  trajectory of each reflector in
  the space
          1992 - SimGraphics
• facial tracking system called a "face waldo.“

• could track the most important motions of the
  face and map them in real-time onto
  computer puppets

• Important: one actor could manipulate all the
  facial expressions of a character by just
  miming the facial expression himself
   SIGGRAPH 1993: Acclaim

• realistic and complex two-character animation
  done entirely with motion capture

• developed a high-performance optical motion
  tracking system able to track up to a 100
  points simultaneously in real-time

• used the system to generate character
  motion sequences for video games
      Optical Motion Capture
• History              Data Acquisition
• State-of-the Art
   – Hardware /
      Software
   – Data Collection
      Algorithms
   – Pros & Cons
• Future
      Optical Motion Capture
• History              Data Translation
• State-of-the Art
   – Hardware /
      Software
   – Data Collection
      Algorithms
   – Pros & Cons
• Future
      Optical Motion Capture
• History              Data Implementation
• State-of-the Art
   – Hardware /
      Software
   – Data Collection
      Algorithms
   – Pros & Cons
• Future
  Data Collection Algorithms
• History              •   Cameras placed around center of room
• State-of-the Art     •   Recording at 320x240 @ 15fps
   – Hardware /        •   Cameras calibrated into common
                           coordinate system
      Software
                       •   Voxel-based volume rendered through a
   – Data Collection       space-carving technique
      Algorithms
                       •   Also uses color-consistency to enhance
   – Pros & Cons           quality
• Future
  Data Collection Algorithms
• History              •   Run a quick test to determine
• State-of-the Art         if the point lies on, in, or
   – Hardware /            outside the shape
      Software
                       •   Moment analysis is then used
   – Data Collection
      Algorithms           to determine other information
   – Pros & Cons           about the point
• Future               •    The fitting error is then found

                       •   A split and merge technique is
                           used to recreate the volume
  Data Collection Algorithms
• History              •   The whole voxel volume is
                           approximated as one ellipsoid
• State-of-the Art     •   It is subdivided into two ellipsoids so
   – Hardware /            D is less than some threshold value
      Software         •   A new voxel set is created from a
   – Data Collection       pairing of voxel sets and neighboring
                           sets
      Algorithms       •   A novel ellipsoid is paired with this
   – Pros & Cons           new set
• Future               •   D is computed, the smallest D value
                           is used to replace the two ellipsoids
                           its replacing
                       •   This is performed only at the first
                           time step to reduce error in merging
  Data Collection Algorithms
• History              •   Problems arise when there are
• State-of-the Art         differing numbers of ellipsoids
   – Hardware /            from one time step to the next
      Software
                       •   ellipsoid sets are merged
   – Data Collection
      Algorithms
   – Pros & Cons
• Future
  Data Collection Algorithms
• History              •   To identify rigid body structures, it
• State-of-the Art         must be known that the mutual
   – Hardware /            Euclidean distance between two
      Software             points will not change if they are in
                           the same rigid body
   – Data Collection
      Algorithms       •   The paths through the time steps are
                           compared in an iterative fashion until
   – Pros & Cons           all ellipsoids are handled
• Future
  Data Collection Algorithms
• History              •   Two adjacent rigid bodies found in
• State-of-the Art         the previous step are used to sample
                           points along any of the three major
   – Hardware /            axes which lie on this ellipse
      Software         •   The number of point samples
   – Data Collection       increases along all three axes
      Algorithms           simultaneously until the average 3D
   – Pros & Cons           location of these points lies within
                           the adjacent ellipse (or vice versa)
• Future
  Pros of Optical Motion Capture
• History              Pros
• State-of-the Art
   – Hardware /
      Software
   – Data Collection
      Algorithms
   – Pros & Cons
• Future
Cons of Optical Motion Capture
• History              Cons
• State-of-the Art
   – Hardware /
      Software
   – Data Collection
      Algorithms
   – Pros & Cons
• Future
                            Current Issues
• History
• State-of-the Art
                          1. Geometric Dissimilarity
• Future
   – Possible solutions        Make human-shaped data
      to current               work on one of these
      problems                 characters, without
   – Possible future           introducing effects of
      paths                    mismatched proportions
                            Current Issues
• History                 2. Different movement
• State-of-the Art           qualities in performers and
• Future                     cartoon characters
   – Possible solutions        Ability to adjust the speeds of
      to current               capture to simulate more
      problems                 cartoon-like movements when
   – Possible future           capturing natural human
      paths                    movement
                            Current Issues
• History
• State-of-the Art
                          3. Increasing data collection
• Future
                             ability
   – Possible solutions
      to current                Make motion capture easier to
      problems                  process with increased
                                technology in the current
   – Possible future
                                software
      paths
                            Current Issues
• History                 4. Increased number of
• State-of-the Art           performers which can be
• Future                     captured simultaneously
   – Possible solutions        Ability to capture groups of
      to current               performers with out reducing
      problems
                               the image quality
   – Possible future
      paths
                                Future Paths
• History                  enhancement of performance
                          conditions through lack of tethering
• State-of-the Art
                          and simplification of performance
• Future                  apparel
   – Possible solutions
      to current           increased speed of the technology
      problems
   – Possible future       increased 'volume' or area in which
      paths               performances can be captured

                           lower cost, so that consumers and
                          independent artists can have access
                          & experiment / expand the technology
                                Future Paths
• History                   increased accuracy of the
• State-of-the Art        results, including improved
• Future                  physical abilities, so that
   – Possible solutions   characters can touch each other
      to current          and feet meet solidly on the ground
      problems
   – Possible future       greater ability to capture data
      paths               from multiple characters

                           combination of virtual reality and
                          existing motion capture technologies
                          could aid in technological development
 Discussion Questions
1. Should using motion capture for
   animation be considered art?
2. Could motion capture be used to create
   realistic human motion in robotics?
3. What would be some other ways to
   capture motion? Audio?
4. Four

								
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