Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks

Balint Antal

Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks

Computer Vision and Pattern Recognition 2016-08-02 v1

Authors: Balint Antal

Abstract

In this paper, an automatic approach to predict 3D coordinates from stereo laparoscopic images is presented. The approach maps a vector of pixel intensities to 3D coordinates through training a six layer deep neural network. The architectural aspects of the approach is presented and in detail and the method is evaluated on a publicly available dataset with promising results.

Keywords

image reconstruction 3d reconstruction pose estimation

Cite

@article{arxiv.1608.00203,
  title  = {Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks},
  author = {Balint Antal},
  journal= {arXiv preprint arXiv:1608.00203},
  year   = {2016}
}

Comments

In Proceedings of the 6th International Joint Conference on Pervasive and Embedded Computing and Communication Systems (PECCS 2016), pages 116-121 ISBN: 978-989-758-195-3

Automatic 3D Point Set Reconstruction from Stereo Laparoscopic Images using Deep Neural Networks

Abstract

Keywords

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