Template matching for large transformations

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Abstract

Finding a template image in another larger image is a problem that has applications in many vision research areas such as models for object detection and tracking. The main problem here is that under real-world conditions the searched image usually is a deformed version of the template, so that these deformations have to be taken into account by the matching procedure. A common way to do this is by minimizing the difference between the template and patches of the search image assuming that the template can undergo 2D affine transformations. A popular differential algorithm for achieving this has been proposed by Lucas and Kanadì [1], with the disadvantage that it works only for small transformations. Here we investigate the transformation properties of a differential template matching approach by using resolution pyramids in combination with transformation pyramids, and show how we can do template matching under large-scale transformations, with simulation results indicating that the scale and rotation ranges can be doubled using a 3 stage pyramid. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Eggert, J., Zhang, C., & Körner, E. (2007). Template matching for large transformations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4669 LNCS, pp. 169–179). Springer Verlag. https://doi.org/10.1007/978-3-540-74695-9_18

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