2D Lattice Extraction from Structured Environments

In this paper we investigate the problem of automatically detecting 2D grid structures such as windows on building facades from images taken in urban settings. The key assumption that the background is strongly structured allows searching for near-regular textures in the image. We describe a probabilistic framework using Markov Random Field modeling and Markov Chain Monte Carlo (MCMC) optimization to explicitly recognize and group rectangular structures that appear in a grid-like pattern. Results on a variety of images of building facades are shown.

[1]  Jens Michael Carstensen,et al.  Bayesian Grid Matching , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  W. K. Hastings,et al.  Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .

[3]  Adrian Barbu,et al.  Generalizing Swendsen-Wang to sampling arbitrary posterior probabilities , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Yanxi Liu,et al.  Tracking Dynamic Near-Regular Texture Under Occlusion and Rapid Movements , 2006, ECCV.

[5]  Luc Van Gool,et al.  Efficient grouping under perspective skew , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[6]  Helmut Mayer,et al.  BUILDING FACADE INTERPRETATION FROM IMAGE SEQUENCES , 2005 .

[7]  Feng Han,et al.  Bottom-up/top-down image parsing by attribute graph grammar , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[8]  Frank Dellaert,et al.  Line-Based Structure from Motion for Urban Environments , 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

[9]  Andrew Zisserman,et al.  A Statistical Approach to Texture Classification from Single Images , 2004, International Journal of Computer Vision.

[10]  Frank Dellaert,et al.  MCMC-based particle filtering for tracking a variable number of interacting targets , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Andrew Zisserman,et al.  Geometric Grouping of Repeated Elements within Images , 1999, Shape, Contour and Grouping in Computer Vision.

[12]  Stan Z. Li,et al.  Markov Random Field Modeling in Computer Vision , 1995, Computer Science Workbench.

[13]  Margrit Betke,et al.  MosaicShape: stochastic region grouping with shape prior , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[14]  Jana Kosecka,et al.  Extraction, matching and pose recovery based on dominant rectangular structures , 2003, HLK.

[15]  Alexei A. Efros,et al.  Discovering Texture Regularity as a Higher-Order Correspondence Problem , 2006, ECCV.

[16]  Frank Dellaert,et al.  A Probabilistic Approach to the Semantic Interpretation of Building Facades , 2004 .