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Title of Journal: Int J Comput Vis

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Abbravation: International Journal of Computer Vision

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Publisher

Springer US

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DOI

10.1007/bf02466670

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1573-1405

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Geometric Image Parsing in ManMade Environments

Authors: Elena Tretyak Olga Barinova Pushmeet Kohli Victor Lempitsky
Publish Date: 2011/09/08
Volume: 97, Issue: 3, Pages: 305-321
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Abstract

We present a new optimization based parsing framework for the geometric analysis of a single image coming from a manmade environment This framework models the scene as a composition of geometric primitives spanning different layers from low level edges through midlevel lines segments lines and vanishing points to high level the zenith and the horizon The inference in such a model thus jointly and simultaneously estimates a the grouping of edges into the line segments b the grouping of line segments into the straight lines c the grouping of lines into parallel families and d the positioning of the horizon and the zenith in the image Such a unified treatment means that the uncertainty information propagates between the layers of the model This is in contrast to most previous approaches to the same problem which either ignore the middle levels line segments or lines all together or use the bottomup stepbystep pipelineFor the evaluation we consider a publicly available York Urban dataset of “Manhattan” scenes and also introduce a new harder dataset of 103 urban outdoor images containing many nonManhattan scenes The comparative evaluation for the horizon estimation task demonstrate higher accuracy and robustness attained by our method when compared to the current stateoftheart approaches

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  1. Growing Regression Tree Forests by Classification for Continuous Object Pose Estimation
  2. Objects, Actions, Places
  3. Hierarchical Shape Segmentation and Registration via Topological Features of Laplace-Beltrami Eigenfunctions
  4. On Taxonomies for Multi-class Image Categorization
  5. Full and Partial Symmetries of Non-rigid Shapes
  6. A Two-Layer Framework for Piecewise Linear Manifold-Based Head Pose Estimation
  7. Learning Discriminative Space–Time Action Parts from Weakly Labelled Videos
  8. Recognizing Fine-Grained and Composite Activities Using Hand-Centric Features and Script Data
  9. 3D Human Pose Tracking Priors using Geodesic Mixture Models
  10. Exemplar-Guided Similarity Learning on Polynomial Kernel Feature Map for Person Re-identification
  11. Ethnicity- and Gender-based Subject Retrieval Using 3-D Face-Recognition Techniques
  12. A Variational Approach to Video Registration with Subspace Constraints
  13. The Fisher-Rao Metric for Projective Transformations of the Line
  14. Planar Motion Estimation and Linear Ground Plane Rectification using an Uncalibrated Generic Camera
  15. Guest Editorial: Human Activity Understanding from 2D and 3D Data
  16. Fast and Stable Polynomial Equation Solving and Its Application to Computer Vision
  17. Robust Pose Recognition of the Obscured Human Body
  18. Teichmüller Shape Descriptor and Its Application to Alzheimer’s Disease Study
  19. Parsing Images into Regions, Curves, and Curve Groups
  20. Using Biologically Inspired Features for Face Processing
  21. Two-View Motion Segmentation with Model Selection and Outlier Removal by RANSAC-Enhanced Dirichlet Process Mixture Models
  22. Information-Theoretic Active Polygons for Unsupervised Texture Segmentation
  23. Virtual Volumetric Graphics on Commodity Displays Using 3D Viewer Tracking
  24. 3-D Symmetry Detection and Analysis Using the Pseudo-polar Fourier Transform
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