Depth Estimation from Image Structure
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Camera Calibration from a Single Manhattan Image
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Manhattan world: orientation and outlier detection by Bayesian inference
Neural Computation
Orientation in Manhattan: Equiprojective Classes and Sequential Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An efficient detection of vanishing points using inverted coordinates image space
Pattern Recognition Letters
Hierarchical building recognition
Image and Vision Computing
Image-based street-side city modeling
ACM SIGGRAPH Asia 2009 papers
3D reconstruction of indoor and outdoor building scenes from a single image
Proceedings of the 2010 ACM workshop on Surreal media and virtual cloning
Geometric image parsing in man-made environments
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
A dynamic programming approach to reconstructing building interiors
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Technical Section: An architectural approach to efficient 3D urban modeling
Computers and Graphics
Simultaneous estimation of vanishing points and their converging lines using the EM algorithm
Pattern Recognition Letters
Vanishing point detection using cascaded 1D Hough Transform from single images
Pattern Recognition Letters
Applications of Geometry Processing: Grammar-based 3D facade segmentation and reconstruction
Computers and Graphics
Geometric Image Parsing in Man-Made Environments
International Journal of Computer Vision
Capturing indoor scenes with smartphones
Proceedings of the 25th annual ACM symposium on User interface software and technology
Multispectral piecewise planar stereo using Manhattan-world assumption
Pattern Recognition Letters
21/2D scene reconstruction of indoor scenes from single RGB-D images
CCIW'13 Proceedings of the 4th international conference on Computational Color Imaging
Vanishing points estimation and line classification in a manhattan world
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
An accurate method for line detection and manhattan frame estimation
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Exploiting depth camera for 3D spatial relationship interpretation
Proceedings of the 4th ACM Multimedia Systems Conference
Structured light self-calibration with vanishing points
Machine Vision and Applications
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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 indoor and outdoor (city) scenes are designed on a Manhattan three-dimensional grid. This Manhattan grid structure puts strong constraints on the intensity gradients in the image. We demonstrate an algorithm for detecting the orientation of the user in such scenes based on Bayesian inference using statistics which we have learnt in this domain. Our algorithm requires a single input image and does not involve pre-processing stages such as edge detection and Hough grouping. We demonstrate strong experimental results on a range of indoor and outdoor images. We also show that estimating the grid structure makes it significantly easier to detect target objects which are not aligned with the grid.