The Cascaded Hough Transform as Support for Grouping and Finding Vanishing Points and Lines
AFPAC '97 Proceedings of the International Workshop on Algebraic Frames for the Perception-Action Cycle
The Cascaded Hough Transform as an Aid in Aerial Image Interpretation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Modelling and Interpretation of Architecture from Several Images
International Journal of Computer Vision
On Symmetry and Multiple-View Geometry: Structure, Pose, and Calibration from a Single Image
International Journal of Computer Vision
Procedural modeling of buildings
ACM SIGGRAPH 2006 Papers
ACM SIGGRAPH Asia 2008 papers
Image-based street-side city modeling
ACM SIGGRAPH Asia 2009 papers
Fixed-Point Continuation for $\ell_1$-Minimization: Methodology and Convergence
SIAM Journal on Optimization
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Detecting large repetitive structures with salient boundaries
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
A Singular Value Thresholding Algorithm for Matrix Completion
SIAM Journal on Optimization
TILT: transform invariant low-rank textures
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
IEEE Transactions on Pattern Analysis and Machine Intelligence
Translation symmetry detection in a fronto-parallel view
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
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In this paper, we propose a shadow-free TILT method to rectify facade images corrupted by shadows. The proposed method is deduced from the original TILT, and improve it by introducing a multiplicative shadow factor. That is, in our method, the constraint is represented that the rectified image equals to the low-rank image multiplied by the shadow image, yet with the additive noise corruption. Moreover, the objective function is improved by incorporating the smooth shadow model. Experimental results on both synthetic and real images demonstrate that our method provides more accurate and stable rectification results as compared with the original TILT, especially when shadows are strong in the input images.