Error Metric Model for 3D Point Cloud Reconstruction Based on Binocular Vision

doi:10.13474/j.cnki.11-2246.2017.0349

Abstract

Abstract: Rapid extraction and construction of 3D model from the images play an important role in the spatial data acquisition. Considering the basic data of smart city construction, how to measure and ensure the accuracy of images-based 3D model reconstruction will become one of research questions. Firstly, the model of 3D point cloud reconstruction need to be studied, and then binocular vision 3D point cloud error metric model and quantitative expression method can be constructed, based on the matrix theory and differential covariance propagation law. This research would provide a theoretical basis for the quality control of 3D image modeling and accuracy assessment.

Key words: binocular vision, 3D point cloud, error, covariance propagation

CLC Number:

P237

BIAN Yuxia, LIU Xuejun, WANG Meizhen, ZHOU Ye, ZHEN Yan. Error Metric Model for 3D Point Cloud Reconstruction Based on Binocular Vision[J]. 测绘通报, 2017, 0(11): 64-67.

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