Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes
We present a method for detecting 3D objects using multi-modalities. While it is generic, we demonstrate it on the combination of an image and a dense depth map which give complementary object information. It works in real-time, under heavy clutter, does not require a time consuming training stage,...
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| creator | Hinterstoisser, S. Holzer, S. Cagniart, C. Ilic, S. Konolige, K. Navab, N. Lepetit, V. |
| description | We present a method for detecting 3D objects using multi-modalities. While it is generic, we demonstrate it on the combination of an image and a dense depth map which give complementary object information. It works in real-time, under heavy clutter, does not require a time consuming training stage, and can handle untextured objects. It is based on an efficient representation of templates that capture the different modalities, and we show in many experiments on commodity hardware that our approach significantly outperforms state-of-the-art methods on single modalities. |
| doi_str_mv | 10.1109/ICCV.2011.6126326 |
| format | Conference Proceeding |
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| ispartof | 2011 International Conference on Computer Vision, 2011, p.858-865 |
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| language | eng |
| recordid | cdi_ieee_primary_6126326 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Robustness |
| title | Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes |
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