Title: Study on feature points matching method based on coding network for portable visual metrology
Abstract: Portable visual metrology works with multiple uncalibrated images and image feature points need to be matched by epipolar geometry.Due to the existence of image distortion,fundamental matrix can't be accurately solved.In order to resolve this problem,a novel indirect fundamental matrix solving method based on coding network geometry is proposed.In this method,spatial interaction collinear mathematical model is established by using automatic error-free correspondence of coding points firstly.Secondly,after being optimized,the strong coding network geometry is built accurately.Meanwhile,the internal and external orientation parameters of each station are optimized accurately.Thirdly,the fundamental matrix can be solved indirectly with the relationship between fundamental matrix and these parameters.Finally,feature points from multi-view can be matched correctly by using the recovered epipolar geometry.Experiments are done for the verification of this method.Compared with v-star,the average error and mean square error of establishing coding network are 0.051 85mm and 0.020 89mm,respectively.Besides,the right matching rate and epipolar geometry recovering accuracy of this method are compared with those of two classic methods,including iterative levenberg-marquardt method and robust LMedS method.Extensive experimental results prove that this method can recover the epipolar geometry accurately and find more matches.
Publication Year: 2014
Publication Date: 2014-01-01
Language: en
Type: article
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