Research of Camera Calibration Based on Genetic Algorithm BP Neural Network

被引：0
|
作者：
Yao, Hengfeng [1 ]
Zhang, Zhibin [1 ]
机构：
[1] Inner Mongolia Univ, Coll Comp Sci, Hohhot, Inner Mongolia, Peoples R China
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION (ICIA) | 2016年
关键词：
back propagation; neural network; camera calibration; genetic algorithm;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Camera calibration is necessary in machine vision application field. Calibration model has nonlinear characteristics, and establishment of mathematical model is often a complicated process, but neural network can solve the complex nonlinear problem effectively, neural network has strong nonlinear approximation ability, adaptive network parameters and fast learning. This paper presents a neurocalibration approach about camera calibration based on back propagation (BP) neural network optimized by genetic algorithm (GA), GA can optimize net parameters about connection weights and threshold values. Making a comprehensive comparison between GA-BP neural network and BP neural network. The experimental results show that the GABP neurocalibration can be effective and feasible by this way.
引用
收藏
页码：350 / 355
页数：6
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