It is the official implementation of paper ''Semantic Object Reconstruction via Casual Handheld Scanning''.
The code was developed by Microsoft Visual Studio 2015 on Windows 10.
Requirements:
- DirectX SDK June 2010
- Kinect SDK (prev. to 2.0)
- NVIDIA CUDA 8.0 (for the CUDA implementation)
- PCL-1.8.0
Optional:
- Kinect SDK (2.0 and above)
- Prime sense SDK
Our method takes RGB images, depth images, and part label images as input, and produces a reconstructed semantic object as output. In our paper, we conducted experiments using the Redwood dataset. This dataset contains only RGB-D scans; the labels can be obtained using any pre-trained neural network. All the images are organized as follows:
|--parent folder
|--depth (*.png)
|--rgb (*.jpg)
|--label (*.png)
If you have any question, please feel free to contact me (cheng.wen.bts@gmail.com).
If you find our work useful in your research, please consider citing:
@article{hu2018semantic,
title={Semantic object reconstruction via casual handheld scanning},
author={Hu, Ruizhen and Wen, Cheng and Van Kaick, Oliver and Chen, Luanmin and Lin, Di and Cohen-Or, Daniel and Huang, Hui},
journal={ACM Transactions on Graphics (TOG)},
volume={37},
number={6},
pages={1--12},
year={2018},
publisher={ACM New York, NY, USA}
}
The code is released under MIT License (see LICENSE file for details).