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Video And Mesh Processing for 3D Cinematography

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Title: Video And Mesh Processing for 3D Cinematography


1
Video And Mesh Processing for 3D Cinematography
  • Remi Ronfard
  • INRIA Rhone-Alpes
  • VAMP Associate Team
  • March 2006

2
Plan of presentation
  • What is 3D cinematography?
  • Goal statement for VAMP
  • People in VAMP
  • Work Items in VAMP
  • Joint activities in 2005
  • Joint activities in 2006
  • Future work and applications

3
What is 3D Cinematography?
  • 3D cinematography, also sometimes called
    free-viewpoint video, is the process of building
    3D models of dynamic scenes from multiple video
    camera inputs.
  • This is an area of active research with enormous
    potential applications in education,
    entertainment, interactive television,
    video-conferencing, etc.
  • It is one of three scenarios actively
    investigated by MPEG for future extensions of
    their audio and video coding standards to 3D
    (3DAV).

4
Goal statement
  • Our teams at INRIA and Brown University have
    separately developped methods and tools for 3D
    photography
  • Moving to 3D cinematography raises difficult
    technological and scientific challenges, where we
    need to collaborate actively.
  • In this new application, the processing pipeline
    must be fully automated, so that 3D
    reconstruction can be performed at video frame
    rates.

5
Goal statement
  • The goal of the associate team is to contribute
    to 3D cinematography by joint work in two crucial
    areas
  • real-time video processing for large networks of
    camera systems, using distributed/parallel and
    embedded architectures
  • real-time mesh processing for reconstruction,
    deformation, texturing and view interpolation of
    3D objects from multiple video, using
    multi-resolution models amenable to efficient,
    scalable compression.

6
Real-time video processing for multiple cameras
  • The goal of the associate team is to develop and
    share software and hardware for the 3D
    cinematography systems built separately by INRIA
    and Brown University.
  • Parallelization/embedding of dedicated algorithms
    for solving problems of camera calibration,
    background subtraction, feature extraction,
    feature matching and so forth.
  • Extend algorithms to dynamic cameras at multiple
    resolutions and viewpoints.

7
Real-time mesh processing of 3D objects
  • Our goal is to obtain high quality approximations
    of the deforming surfaces of objects in a dynamic
    scene at any point in time, and to render them by
    projecting video textures on them.
  • Subdivision surfaces and their multi-resolution
    extensions are the right tools for achieving both
    high-quality renderings, which are necessary to
    convey the illusion of reality, and
    high-compression ratios, which are necessary to
    overcome the massive amounts of data involved in
    multiple-view video.
  • This necessitates substantial extensions of the
    current state-of-the art in both computer vision
    and graphics, since the projective constraints
    arising from multiple cameras are essentially
    non-linear.

8
Team Composition
  • The associate team is composed of 5 senior
    researchers, 10 PhD students and 2 engineers.
  • Gabriel Taubin and 4 students at Brown (EE)
  • Peter Sibley, Daniel Crispell, Yong Zhao, Douglas
    Lanman
  • Chad Jenkins and 3 students at Brown (CS)
  • Matt Loper, German Gonzales, Dan Grollman
  • Rémi Ronfard and 2 students at INRIA (MOVI)
  • David Knossow, Daniel Weinland
  • Edmond Boyer and 1 student (MOVI)
  • Clement Menier
  • Frederic Devernay, Loic Lefort and Herve Mathieu

9
Previous work
  • Gabriel Taubin and Rémi Ronfard has a close
    collaboration at IBM TJ Watson Research Center in
    1992 and 2000 on efficient data structures and
    algorithms for manipulating multi-resolution
    curves and surfaces
  • Gabriel Taubin, Remi Ronfard Implicit simplical
    models for adaptive curve reconstruction. IEEE
    transactions on Pattern Analysis and Machine
    Intelligence, 3(18), pp. 321-325, 1996
  • Ioana Martin, Remi Ronfard, Fausto Bernardini
    Detail-Preserving Variational Surface Design with
    Multiresolution Constraints. International
    Conference on Shape Modeling and Applications,
    June 2004.

10
Team Complementarity
  • The MOVI team at INRIA brings expertise in camera
    calibration and synchronization multiple-view
    stereo and shape from silhouette real-time and
    distributed systems action recognition.
  • The two teams at Brown bring complementary
    expertise in embedded systems programming and
    image-based rendering, mesh processing, machine
    learning and behaviour-based robotics.

11
Initial work items
  • Distributed video capture, including camera
    synchronization and calibration
  • Multi-resolution object surfaces from silhouettes
    using subdivision surfaces, with applications on
    modeling deformable objects and interpolating new
    viewpoints
  • Human motion tracking and action understanding

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15
Blinky Distributed Camera Control
16
Camera Recording and Playback
17
Camera Calibration
18
3D models from multiple views
  • Visual Hulls and Shapes (Edmond Boyer)

19
From multiple cameras to 3D
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21
Beyond visual hulls and towards multi-resolution
(work in progress)
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26
Markerless articulated motion
27
Human Action Recognition
28
Human action recognition example
29
Recovering body skeleton from video (work in
progress)
30
Achievement in 2005
  • June/July 2005 - The initial associate team
    meetings were very successful and appealed to PhD
    students enormously on both sides.
  • Those meetings revealed that both labs are
    heading very rapidly towards very large camera
    arrays (100's at INRIA, 1000's at Brown).
  • Although the initial investment in terms of
    hardware and software developments are still
    high, our collaboration will save efforts and
    expenses.
  • INRIA recording and playback software has been
    deployed at Brown for initial experiments,
    calibration and background subtraction to follow

31
Exchanges in 2005

32
Scheduled exchanges in 2006
  • Chad Jenkins will visit INRIA in April
  • continue ongoing collaboration with Clement
    Menier on medial-axis reconstruction from
    multiple silhouettes
  • start a new collaboration with Daniel Weinland on
    motion modeling and action recognition.
  • In June, Gabriel Taubin and Remi Ronfard host an
    international workshop on 3D cinematography at
    CVPR in New York City.
  • More student exchanges throughout summer (thanks
    to NSF)
  • multi-resolution surface from silhouettes
  • multi-view stereo, deformable surfaces

33
Scheduled exchanges for 2006

   
34
Future work Cinematized Reality
  • Track and follow action
  • Tracking paths of multiple people
  • Tracking articulated motion
  • Tracking activities
  • Generate new views
  • View-dependent textures mapped to 3D model
  • Camera placement problem - How to choose the best
    views ?
  • Generate new movies in 2D or 3D

35
Applications
  • Digitizing Live Performances
  • Cultural Heritage and Education
  • Interactive Television, Games
  • Holographic theatre
  • Tele-presence
  • Remote actors, dancers, musicians
  • Theatre of operations in medecine and military
  • Producing content for 3D cinema (2010) and 3D
    television (2020)

36
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