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Camera Pose Estimation Method Based on Deep Neural Network

Published:05 July 2019Publication History

ABSTRACT

This paper proposes a camera pose estimation algorithm based on deep neural network, which returns the translation and rotation of the camera based on supervised deep learning. This paper uses the ORB algorithm to extract the feature points of the image, and the feature points are labeled on the color image for training and testing. The deep neural network based on the structure of recurrent convolution neural network (RCNN). Firstly, some features extracted by the convolution neural network. Then,it builds the order model base on the RCNN network. The RMS error is used as the loss function to train the network, in which the rotation is expressed by Euler angle. Finally,experiments on KITTI VO dataset show that the proposed method is effective.

References

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  1. Camera Pose Estimation Method Based on Deep Neural Network

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      cover image ACM Other conferences
      ICDLT '19: Proceedings of the 2019 3rd International Conference on Deep Learning Technologies
      July 2019
      106 pages
      ISBN:9781450371605
      DOI:10.1145/3342999

      Copyright © 2019 ACM

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      Publication History

      • Published: 5 July 2019

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