Abstract
Translation symmetry is one of the most important pattern characteristics in natural and man-made environments. Detecting translation symmetry is a grand challenge in computer vision. This has a large spectrum of real-world applications from industrial settings to design, arts, entertainment and eduction. This paper describes the algorithm we have submitted for the Symmetry Detection Competition 2013. We introduce two new concepts in our symmetric repetitive pattern detection algorithm. The first concept is the bottom-up detection-inference approach. This extends the versatility of current detection methods to a higher level segmentation. The second concept is the framework of a new theoretical analysis of invariant repetitive patterns. This is crucial in symmetry/non-symmetry structure extraction but has less coverage in the previous literature on pattern detection and classification.
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