| Authors |
Pirker Katrin, Gerald Schweighofer, Rüther Matthias, Bischof Horst |
| Appeared in |
1st IEEE/ICCV Workshop on Consumer Depth Cameras for Computer Vision |
| Date |
2011 |
| Abstract |
Building a dense and accurate environment model out of range image data faces problems like sensor noise, extensive memory consumption or computation time. We present an approach which reconstructs 3D environments using a probabilistic occupancy grid in real-time. Operating on depth image pyramids speeds up computation time, whereas a weighted interpolation scheme between neighboring pyramid layers boosts accuracy. In our experiments we compare our method with a state-of-the-art mapping procedure. Our results demonstrate that we achieve better results. Finally, we present its viability by mapping a large indoor environment. |
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