校准
人工神经网络
计算机科学
人工智能
集合(抽象数据类型)
计算机视觉
摄影测量学
帧(网络)
数学
电信
统计
程序设计语言
作者
Junfeng Wen,Gerhard Schweitzer
标识
DOI:10.1109/ijcnn.1991.170424
摘要
The authors first discuss the physical and mathematical model of CCD (charge coupled device) cameras on which the standard photogrammetric calibration of the cameras is based. Then they introduce artificial neural networks in order to improve the classical calibration of the CCD cameras, and thus develop a new method to calibrate CCD cameras. In this set-up, a feedforward artificial neural network is used. Three advantages of the hybrid calibration are discussed: feasibility, applicability, and efficiency. In order to judge the quality of the calibration, the calibration error of a camera is defined. It is shown experimentally that the accuracy of the image frame coordinates has been improved by a factor two through the hybrid calibration. It appears to be a new idea to add an artificial neural network to the physical and mathematical model of a system in order to improve the overall description of the system.< >
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