Detecting, Grouping, and Structure Inference for Invariant Repetitive Patterns in Images

The efficient and robust extraction of invariant patterns from an image is a long-standing problem in computer vision. Invariant structures are often related to repetitive or near-repetitive patterns. The perception of repetitive patterns in an image is strongly linked to the visual interpretation and composition of textures. Repetitive patterns are products of both repetitive structures as well as repetitive reflections or color patterns. In other words, patterns that exhibit near-stationary behavior provide rich information about objects, their shapes, and their texture in an image. In this paper, we propose a new algorithm for repetitive pattern detection and grouping. The algorithm follows the classical region growing image segmentation scheme. It utilizes a mean-shift-like dynamic to group local image patches into clusters. It exploits a continuous joint alignment to: 1) match similar patches, and 2) refine the subspace grouping. We also propose an algorithm for inferring the composition structure of the repetitive patterns. The inference algorithm constructs a data-driven structural completion field, which merges the detected repetitive patterns into specific global geometric structures. The result of higher level grouping for image patterns can be used to infer the geometry of objects and estimate the general layout of a crowded scene.

[1]  Leonidas J. Guibas,et al.  Discovering structural regularity in 3D geometry , 2008, ACM Trans. Graph..

[2]  Alan L. Yuille,et al.  Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

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

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

[5]  Yanxi Liu,et al.  Deformed Lattice Detection in Real-World Images Using Mean-Shift Belief Propagation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  P. Olver Applications of Lie Groups to Differential Equations , 1986 .

[7]  B. Julesz Textons, the elements of texture perception, and their interactions , 1981, Nature.

[8]  Yanxi Liu,et al.  A Lattice-Based MRF Model for Dynamic Near-Regular Texture Tracking , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Roland Siegwart,et al.  Exploiting Repetitive Object Patterns for Model Compression and Completion , 2010, ECCV.

[10]  Sridha Sridharan,et al.  Least squares congealing for unsupervised alignment of images , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Erik G. Learned-Miller,et al.  Data driven image models through continuous joint alignment , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Jitendra Malik,et al.  Detecting, localizing and grouping repeated scene elements from an image , 1996, ECCV.

[13]  Yanxi Liu,et al.  Quantitative Evaluation of Near Regular Texture Synthesis Algorithms , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[14]  Hagit Hel-Or,et al.  Symmetry as a Continuous Feature , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Lance R. Williams,et al.  Stochastic Completion Fields: A Neural Model of Illusory Contour Shape and Salience , 1997, Neural Computation.

[16]  Andrew Zisserman,et al.  Geometric Grouping of Repeated Elements within Images , 1998, BMVC.

[17]  George Baciu,et al.  Higher level segmentation: Detecting and grouping of invariant repetitive patterns , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[18]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Richard G. Baraniuk,et al.  The multiscale structure of non-differentiable image manifolds , 2005, SPIE Optics + Photonics.

[20]  George Baciu,et al.  Inferring repeated pattern composition in near regular textures , 2012, 2012 19th IEEE International Conference on Image Processing.

[21]  Jan-Olof Eklundh,et al.  Detecting Symmetry and Symmetric Constellations of Features , 2006, ECCV.

[22]  Luc Van Gool,et al.  Computational Symmetry in Computer Vision and Computer Graphics , 2010, Found. Trends Comput. Graph. Vis..

[23]  Jan-Michael Frahm,et al.  Detecting Large Repetitive Structures with Salient Boundaries , 2010, ECCV.

[24]  Yanxi Liu,et al.  Near-regular texture analysis and manipulation , 2004, SIGGRAPH 2004.

[25]  George Baciu,et al.  Detection of repetitive patterns in near regular texture images , 2011, 2011 IEEE 10th IVMSP Workshop: Perception and Visual Signal Analysis.