Zhao Zhangyan

TL;DR: The method described in this paper significantly improves the accuracy of the measuring results of photogrammetry while photos used for the calculation were taken at unsatisfactory angles and distances caused by the limitation of the port condition.

TL;DR: This work proposes a robust and accurate camera pose determination method based on geometric optimization search using the Internet of Things that performs well on both synthetic and real data and can be used to provide accurate and stable data for subsequent applications.

TL;DR: In this article, a photogrammetric algorithm was proposed to improve the precision of the measurement data by adopting an intersection point prediction algorithm and introducing redundant observation, and a weighting algorithm based on an existing lens optical distortion model was given for further improving the precision, while a set of iteration rules were established by adopting a threshold value setting method based on the weighting, so that quality of calculation results are controllable.

TL;DR: In this article, a fuzzy matching method for the photogrammetry of a port crane is presented, which includes the steps of calculating coordinates of an image plane coordinate system of each to-be-measured point as a key point according to an estimated parametric model and left and right exterior orientation elements.

TL;DR: In this article, a large portal crane beam deformation measuring method based on an image and a geometric contour is proposed, which consists of first acquiring different contour lines of a crane beam to obtain sequence image data; carrying out data preprocessing, and extracting the contours lines of the crane beam in the image; computing initial values of the length, the width and the center coordinates of a rectangular cross section of the cranes beam; selecting a corresponding photo from a photo sequence through the transverse length of the given crane beam, carrying out iterative computation to obtain the