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ICCV
1999
IEEE
14 years 6 months ago
Manhattan World: Compass Direction from a Single Image by Bayesian Inference
When designing computer vision systems for the blind and visually impaired it is important to determine the orientation of the user relative to the scene. We observe that most ind...
James M. Coughlan, Alan L. Yuille
NIPS
2000
13 years 5 months ago
The Manhattan World Assumption: Regularities in Scene Statistics which Enable Bayesian Inference
Preliminary work by the authors made use of the so-called "Manhattan world" assumption about the scene statistics of city and indoor scenes. This assumption stated that ...
James M. Coughlan, Alan L. Yuille
CVPR
2012
IEEE
11 years 7 months ago
Robust camera self-calibration from monocular images of Manhattan worlds
We focus on the detection of orthogonal vanishing points using line segments extracted from a single view, and using these for camera self-calibration. Recent methods view this pr...
Horst Wildenauer, Allan Hanbury
ECCV
2002
Springer
14 years 6 months ago
Automatic Camera Calibration from a Single Manhattan Image
We present a completely automatic method for obtaining the approximate calibration of a camera (alignment to a world frame and focal length) from a single image of an unknown scene...
J. Deutscher, Michael Isard, John MacCormick
ICIP
2003
IEEE
14 years 6 months ago
Navigating in Manhattan: 3D orientation from video without correspondences
The problem of inferring 3D orientation of a camera from video sequences has been mostly addressed by first computing correspondences of image features. This intermediate step is ...
André F. T. Martins, Mário A. T. Fig...