Multimodal Templates for Real-Time Detection of Texture-Less Objects in Heavily Cluttered Scenes
Abstract
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.
Cite
Text
Hinterstoisser et al. "Multimodal Templates for Real-Time Detection of Texture-Less Objects in Heavily Cluttered Scenes." IEEE/CVF International Conference on Computer Vision, 2011. doi:10.1109/ICCV.2011.6126326Markdown
[Hinterstoisser et al. "Multimodal Templates for Real-Time Detection of Texture-Less Objects in Heavily Cluttered Scenes." IEEE/CVF International Conference on Computer Vision, 2011.](https://mlanthology.org/iccv/2011/hinterstoisser2011iccv-multimodal/) doi:10.1109/ICCV.2011.6126326BibTeX
@inproceedings{hinterstoisser2011iccv-multimodal,
title = {{Multimodal Templates for Real-Time Detection of Texture-Less Objects in Heavily Cluttered Scenes}},
author = {Hinterstoisser, Stefan and Holzer, Stefan and Cagniart, Cedric and Ilic, Slobodan and Konolige, Kurt and Navab, Nassir and Lepetit, Vincent},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2011},
pages = {858-865},
doi = {10.1109/ICCV.2011.6126326},
url = {https://mlanthology.org/iccv/2011/hinterstoisser2011iccv-multimodal/}
}