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2009
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Distance Transform Templates for Object Detection and Pose Estimation

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Distance Transform Templates for Object Detection and Pose Estimation
We propose a new approach for detecting low textured planar objects and estimating their 3D pose. Standard matching and pose estimation techniques often depend on texture and feature points. They fail when there is no or only little texture available. Edge-based approaches mostly can deal with these limitations but are slow in practice when they have to search for six degrees of freedom. We overcome these problems by introducing the Distance Transform Templates, generated by applying the distance transform to standard edge based templates. We obtain robustness against perspective transformations by training a classifier for various template poses. In addition, spatial relations between multiple contours on the template are learnt and later used for outlier removal. At runtime, the classifier provides the identity and a rough 3D pose of the Distance Transform Template, which is further refined by a modified template matching algorithm that is also based on the distance ...
Stefan Holzer, Stefan Hinterstoisser, Slobodan Ili
Added 23 Jul 2009
Updated 10 Dec 2009
Type Conference
Year 2009
Where CVPR
Authors Stefan Holzer, Stefan Hinterstoisser, Slobodan Ilic, Nassir Navab
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