• Name: Philippe Beaudoin
  • Login Name: beaudoin
  • Email: beaudoin@csDELETEthisTEXT.ubc.ca
  • Phone: (604) 827-3992
  • Office: X653
  • Lab: X660 (Imager lab)
  • Comment: Post-Doc with Michiel van de Panne in the Imager Lab (until January 2010).

About Me

Philippe Beaudoin
I completed a Ph. in computer graphics at University of Montreal under the supervision of Pierre Poulin. My main research interest is data-driven character animation.


Animation People at UBC

Teaching links

Summer Project Ideas

  • Some very abstract ideas...
    • When compressing, study if similar motions have a similar optimal truncated wavelet coefficient distribution.
    • If so, then use this fact (together with PCA?) to reduce the search space for various kinematic motion synthesis.
  • Throwing and catching
    • Acquire mocap data for a character catching an object (a ball?)
    • Parameterize on:
      • Catching location
      • Object speed and mass
    • Kinematically synthesize a novel motion given arbitrary parameters
  • Efficient real-time exploration of a distant motion-capture database
    • Motions are transmitted across a slow channel (ie. the internet)
    • Simultaneously display a bunch of huge bunch of animations (on the same ground plane, with a wide perspective view)
    • Use wavelet-based progressive motion compression to obtain adaptive level-of-detail
      • Motion far from the viewer is less detailed
      • Automatic and nice degradation when transmission slows down
    • Use streaming transmission
    • Spatially regroup animations according to similarity
    • Automatixally extract a motion hierarchy based on similarity
      • Display a sample motion for a a complete group of similar motion that can later be "opened up"
  • Compression related projects
    • Develop and study more involved spatial compressions
      • PCA across the DOFs with pre- or post-wavelet compression (useful for large database compression)
      • Use automatic motion segmentation (Barbic et al. 2004) and pre-canned linear spaces adapted to the extracted clip
      • Dictionnary-based methods for large database (problem: building an efficient dictionnary of motion clips)
    • Study the importance of various errors in human perception of skeletal animations
    • Apply compression to complex animation data structures
      • Motion Graphs
      • Specialized database for synthesis of a specific kind of motion
    • Constaint enforcement during compression
      • Constrain extremal poses and derivatives (for inclusion in a "snap-together" style of motion graph, or for cycling motions)
      • 2-person interaction (dancing...) where animations constrain each other.
    • Efficient motion blending using a wavelet basis
    • Develop and study prediction-correction schemes (similar to MPEG motion compensation)
    • Build and use statistical motion models to increase compression efficiency
      • The model could be for a complete skeleton or part of a skeleton
      • The model could be specific (extracted from a small bank of similar motions) or generic (extracted from a large motion database)
      • The model could be for really short motion segments or for complete clips
      • Better yet, it could be multi-resolution: long clips for wide basis functions and short clips for narrow basis functions.

Personal Interests (beside CG)

Technical Links

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