发明名称 |
METHOD AND SYSTEM FOR AUTOMATICALLY OPTIMIZING QUALITY OF POINT CLOUD DATA |
摘要 |
Disclosed is a method for automatically optimizing point cloud data quality, including the following steps of: acquiring initial point cloud data for a target to be reconstructed, to obtain an initial discrete point cloud; performing preliminary data cleaning on the obtained initial discrete point cloud to obtain a Locally Optimal Projection operator (LOP) sampling model; obtaining a Possion reconstruction point cloud model by using a Possion surface reconstruction method on the obtained initial discrete point cloud; performing iterative closest point algorithm registration on the obtained Possion reconstruction point cloud model and the obtained initial discrete point cloud; and for each point on a currently registered model, calculating a weight of a surrounding point within a certain radius distance region of a position corresponding to the point for the point on the obtained LOP sampling model, and comparing the weight with a threshold, to determine whether a region where the point is located requires repeated scanning. Further disclosed is a system for automatically optimizing point cloud data quality. |
申请公布号 |
US2016125226(A1) |
申请公布日期 |
2016.05.05 |
申请号 |
US201314893035 |
申请日期 |
2013.11.26 |
申请人 |
SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY CHINESE ACADEMY OF SCIENCES |
发明人 |
HUANG Hui |
分类号 |
G06K9/00;G06K9/56;G06K9/20;G06T15/10;G06T7/00;G06K9/62;G06K9/40;G06T19/20 |
主分类号 |
G06K9/00 |
代理机构 |
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代理人 |
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主权项 |
1. A method for automatically optimizing point cloud data quality, comprising the following steps of:
a. acquiring initial point cloud data for a target to be reconstructed, to obtain an initial discrete point cloud; b. performing preliminary data cleaning on the obtained initial discrete point cloud to obtain a Locally Optimal Projection operator (LOP) sampling model; c. obtaining a Possion reconstruction point cloud model by using a Possion surface reconstruction method on the obtained initial discrete point cloud; d. performing iterative closest point algorithm registration on the obtained Possion reconstruction point cloud model and the obtained initial discrete point cloud; and e. for each point on a currently registered model, calculating a weight of a surrounding point within a certain radius distance region of a position corresponding to the point for the point on the obtained LOP sampling model, and comparing the weight with a threshold, to determine whether a region where the point is located requires repeated scanning. |
地址 |
Guangdong CN |