3D Form and Motion: Difference between revisions

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* Suggested by Pulkit:
* Suggested by Pulkit:
** D Ramanan, "Analyzing 3D Objects in Cluttered Images" [http://www.ics.uci.edu/~dramanan/papers/car.pdf pdf]
** D Ramanan, "Analyzing 3D Objects in Cluttered Images" [http://www.ics.uci.edu/~dramanan/papers/car.pdf pdf]
** B Schiele, first couple papers at [http://www.d2.mpi-inf.mpg.de/publications]
** B Schiele, first couple of papers at [http://www.d2.mpi-inf.mpg.de/publications url]
 
'''3D data sets'''
* Princeton Shape data set:  [http://shape.cs.princeton.edu/benchmark/ url]
* Ponce: [http://www-cvr.ai.uiuc.edu/ponce_grp/data/ url]
* Silberman [http://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html url]


'''SLAM:'''
'''SLAM:'''

Revision as of 05:00, 7 April 2013

Mondays at 1:00, Evans 560

3D models from images:

  • Hartley and Zisserman: Multiple View Geometry (Amazon)
  • Hoiem and Savarese: 3D object recognition and scene interpretation, book pdf
  • Hoiem Ph.D. thesis "SEEING THE WORLD BEHIND THE IMAGE" pdf
  • Cashman and Fitzgibbon: "What Shape are Dolphins? Building 3D Morphable Models from 2D Images" pdf
  • Snavely and Seitz (2006), "Photo tourism" (aka photosynth), pdf
  • Seitz google talk on history of 3D computer vision: URL
    • Blanz and Vetter, 3D face models pdf
    • Tomasi and Kanade, factorization of shape and motion, pdf
  • Suggested by Pulkit:
    • D Ramanan, "Analyzing 3D Objects in Cluttered Images" pdf
    • B Schiele, first couple of papers at url

3D data sets

  • Princeton Shape data set: url
  • Ponce: url
  • Silberman url

SLAM:

  • wiki page with list of refs
  • Thrun, "Probabilistic algorithms in robotics" pdf
  • Daniel Cremers work on helicopters/SLAM (TU Munich) URL
  • Newcombe and Davison, "Live dense reconstruction with a single moving camera work on fast single camera", pdf

Psychophysics:

  • Nakayama et al. (1995) "Visual Surface Representation" pdf
  • Glennerster and Fitzgibbon, "View-Based Approaches to Spatial Representation in Human Vision" pdf
  • Wexler work on depth from self-motion/parallax, reference frames, pdf1, pdf2

Action-perception:

  • Philipona et al. Neural Computation (2003) pdf
    • Follow on papers URL
  • Philipona et al. NIPS (2003) pdf
    • Follow on papers URL
  • Polani et al. "From unknown sensors and actuators to actions" pdf
  • Robotics paper trying to perceive environment based on sensiromotor loop (from Pulkit): pdf

Manifolds:

  • Manifolds in computer vision tutorial: pdf
    • references: URL