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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Holzer, S. Hinterstoisser, S. Ilic, S. Navab, N. |
| Copyright Year | 2009 |
| Description | Author affiliation: Dept. of Comput. Sci., Tech. Univ. of Munich (TUM), Garching, Germany (Holzer, S.; Hinterstoisser, S.; Navab, N.) || Deutsche Telekom Labs., Tech. Univ. Berlin, Berlin, Germany (Ilic, S.) |
| Abstract | 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 transform. We qualitatively and quantitatively evaluate our approach on synthetic and real-life examples and demonstrate robust real-time performance. |
| Starting Page | 1177 |
| Ending Page | 1184 |
| File Size | 4078990 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424439928 |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.2009.5206777 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-06-20 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Object detection Robustness Image edge detection Runtime Computer science Laboratories Visualization Layout Least squares methods Pixel |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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