Non-local scan consolidation for 3D urban scenes
ACM SIGGRAPH 2010 papers
Resizing by symmetry-summarization
ACM SIGGRAPH Asia 2010 papers
Translation-symmetry-based perceptual grouping with applications to urban scenes
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Geo-localization of street views with aerial image databases
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Symmetry-guided texture synthesis and manipulation
ACM Transactions on Graphics (TOG)
Visual pattern discovery for architecture image classification and product image search
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Digital reconstruction of halftoned color comics
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Dynamics of a mean-shift-like algorithm and its applications on clustering
Information Processing Letters
Ultra-wide baseline facade matching for geo-localization
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Dynamic markov random field model for visual tracking
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
International Journal of Computer Vision
Scale detection via keypoint density maps in regular or near-regular textures
Pattern Recognition Letters
Lattice estimation from images of patterns that exhibit translational symmetry
Image and Vision Computing
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We propose a novel and robust computational framework for automatic detection of deformed 2D wallpaper patterns in real-world images. The theory of 2D crystallographic groups provides a sound and natural correspondence between the underlying lattice of a deformed wallpaper pattern and a degree-4 graphical model. We start the discovery process with unsupervised clustering of interest points and voting for consistent lattice unit proposals. The proposed lattice basis vectors and pattern element contribute to the pairwise compatibility and joint compatibility (observation model) functions in a Markov Random Field (MRF). Thus, we formulate the 2D lattice detection as a spatial, multitarget tracking problem, solved within an MRF framework using a novel and efficient Mean-Shift Belief Propagation (MSBP) method. Iterative detection and growth of the deformed lattice are interleaved with regularized thin-plate spline (TPS) warping, which rectifies the current deformed lattice into a regular one to ensure stability of the MRF model in the next round of lattice recovery. We provide quantitative comparisons of our proposed method with existing algorithms on a diverse set of 261 real-world photos to demonstrate significant advances in accuracy and speed over the state of the art in automatic discovery of regularity in real images.