{"title":"Research of camera calibration based on genetic algorithm BP neural network","authors":"Hengfeng Yao, Zhibin Zhang","doi":"10.1109/ICINFA.2016.7831849","DOIUrl":null,"url":null,"abstract":"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 GA-BP neurocalibration can be effective and feasible by this way.","PeriodicalId":389619,"journal":{"name":"2016 IEEE International Conference on Information and Automation (ICIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Information and Automation (ICIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINFA.2016.7831849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
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 GA-BP neurocalibration can be effective and feasible by this way.