Geometric Grouping of Repeated Elements within Images

The objective of this work is the automatic detection and grouping of imaged elements which repeat on a plane in a scene (for example tiled floorings). It is shown that structures that repeat on a scene plane are related by particular parametrized transformations in perspective images. These image transformations provide powerful grouping constraints, and can be used at the heart of hypothesize and verify grouping algorithms. The parametrized transformations are global across the image plane and may be computed without knowledge of the pose of the plane or camera calibration. Parametrized transformations are given for severalcl asses of repeating operation in the world as well as groupers based on these. These groupers are demonstrated on a number of real images, where both the elements and the grouping are determined automatically. It is shown that the repeating element can be learnt from the image, and hence provides an image descriptor. Also, information on the plane pose, such as its vanishing line, can be recovered from the grouping.

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