Target identification method and system based on three-dimensional point cloud data

A three-dimensional point cloud, target recognition technology, applied in the field of pattern recognition, to achieve the effect of high accuracy

Inactive Publication Date: 2016-12-21
SHENZHEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Stable local feature combination is suitable for direct feature point matching, and can achieve good results in some scenes, but the use of limited local features to realize the global feature description of objects is still the difficulty of target recognition in complex scenes

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  • Target identification method and system based on three-dimensional point cloud data
  • Target identification method and system based on three-dimensional point cloud data
  • Target identification method and system based on three-dimensional point cloud data

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Embodiment Construction

[0042] It should be noted that the embodiments in the application and the features in the embodiments can be combined with each other if there is no conflict.

[0043] The present invention provides a target recognition method based on three-dimensional point cloud data, which includes the following steps:

[0044] Obtain the circumscribed cuboid for the 3D point cloud data of the marked category;

[0045] Extracting regular geometry from the three-dimensional point cloud data of the marked category;

[0046] Build a model database;

[0047] Build the model data table;

[0048] Enter the point cloud data of the target to be recognized and perform online recognition.

[0049] As an improvement of the technical solution, the step of obtaining the circumscribed cuboid on the three-dimensional point cloud data of the mark category further includes:

[0050] Obtain the direction of each ridge line of the cuboid circumscribed by the point cloud;

[0051] Obtain the circumscribed cuboid of the poi...

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Abstract

The invention discloses a target identification method based on three-dimensional point cloud data. The target identification method comprises the following steps of: carrying out external cuboid obtaining on three-dimensional point cloud data of a marked category; extracting a regular geometry from the three-dimensional point cloud data of the marked category; constructing a model database; constructing a model data table; and inputting point cloud data of a target to be identified and carrying out online identification. A target identification system based on the three-dimensional point cloud data comprises a first module, a second module, a third module, a fourth module and a fifth module, wherein the first module is used for executing external cuboid obtaining on the three-dimensional point cloud data of the marked category; the second module is used for executing extraction of the regular geometry from the three-dimensional point cloud data of the marked category; the third module is used for executing construction of the model database; the fourth module is used for executing construction of the model data table; and the fifth module is used for executing input of the point cloud data of the target to be identified and online identification. The method and the system are convenient and rapid in the target identifying process, and are high in accuracy. The method and the system are widely applied to the technical field of mode identification.

Description

Technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a target recognition method and system based on three-dimensional point cloud data of regular geometric bodies. Background technique [0002] With the rapid development of 3D scanning technology, target recognition based on 3D point cloud data is receiving extensive attention. Target recognition in 3D point cloud data generally includes two stages: feature extraction and feature matching. Object features include global features and local features. Global features describe the overall shape of the object; local features focus more on details and describe more refined features in a small area of ​​the object. Target extraction based on global features is too sensitive to factors such as target deformation and target incompleteness due to occlusion; while some local features have the advantages of scale and rotation invariance, which can solve the above problems to a certain...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06F17/30
CPCG06F16/51G06F16/583G06V20/653G06V10/44G06F18/22G06F18/214
Inventor 田劲东单波田勇李东
Owner SHENZHEN UNIV
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