Camera Pose Estimation Method Based on Deep Neural Network

被引:0
|
作者
Tang Xia Qing [1 ]
Wu Fan [1 ]
Zong Yan Tao [1 ]
机构
[1] Army Acad Armored Forces, 12 Dujiakan Yard, Beijing, Peoples R China
来源
ICDLT 2019: 2019 3RD INTERNATIONAL CONFERENCE ON DEEP LEARNING TECHNOLOGIES | 2019年
关键词
camera pose estimation; feature point extraction; convolutional neural network; recurrent neural network; deep learning; SLAM;
D O I
10.1145/3342999.3343014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:85 / 90
页数:6
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