Computing Local Surface Orientation and Shape from Texture forCurved Surfaces
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope
International Journal of Computer Vision
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Depth Estimation from Image Structure
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Geometric Context from a Single Image
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Putting Objects in Perspective
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Recovering Surface Layout from an Image
International Journal of Computer Vision
Fast Automatic Single-View 3-d Reconstruction of Urban Scenes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Efficient Edge-Based Methods for Estimating Manhattan Frames in Urban Imagery
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Make3D: Learning 3D Scene Structure from a Single Still Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stages as Models of Scene Geometry
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric image parsing in man-made environments
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Monocular 3D scene modeling and inference: understanding multi-object traffic scenes
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Retrieving images of similar geometrical configuration
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Fast anisotropic Gauss filtering
IEEE Transactions on Image Processing
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Significant advances have recently been made in the development of computational methods for predicting 3D scene structure from a single monocular image. However, their computational complexity severely limits the adoption of such technologies to various computer vision and pattern recognition applications. In this paper, we address the problem of inferring 3D scene geometry from a single monocular image of man-made environments. Our goal is to estimate the 3D structure of a scene in real-time with a level of accuracy useful in certain real applications. Towards this end, we decompose the three-dimensional world space into a set of geometrically inspired primitive subspaces. One important advantage of our approach is that the complex estimation problem can be systematically broken down into a sequence of subproblems, which are easier to solve and more reliable even with the presence of occlusion or clutter, without loss of generality. The proposed algorithm also serves as the technical foundation for effective representation of the 3D scene geometry based on a simple description of the textural patterns present in the image and their spatial arrangement. Extensive experiments have been conducted on a large scale challenging dataset of real-world images. Our results demonstrate that the proposed method remarkably outperforms the recent state-of-the-art algorithms with respect to speed and accuracy.