Three-dimensional object recognition method based on multi-view double-attention network

A technology of three-dimensional objects and recognition methods, applied in three-dimensional object recognition, neural learning methods, character and pattern recognition, etc., to achieve the effect of strong characteristic response

Active Publication Date: 2021-05-11
UNIV OF SHANGHAI FOR SCI & TECH
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Problems solved by technology

However, compared with the traditional two-dimensional image classification, there is still a lot of room for imp...

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  • Three-dimensional object recognition method based on multi-view double-attention network
  • Three-dimensional object recognition method based on multi-view double-attention network
  • Three-dimensional object recognition method based on multi-view double-attention network

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Embodiment Construction

[0048] In order to make the technical means and effects realized by the present invention easy to understand, the present invention will be described in detail below in conjunction with the embodiments and accompanying drawings.

[0049]

[0050] figure 1 It is a schematic flowchart of a three-dimensional object recognition method based on a multi-view double attention network in an embodiment of the present invention; figure 2 is a schematic structural diagram of the multi-view dual-attention network in the embodiment of the present invention.

[0051] like figure 1 and figure 2 As shown, a kind of three-dimensional object recognition method based on multi-view double attention network of the present embodiment comprises the following steps:

[0052] Step 1: Project the original 3D object from n perspectives to 2D plane rendering to obtain n views, and perform feature extraction on the n views through the basic CNN model to obtain n visual features.

[0053] Step 1 in...

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Abstract

The invention provides a three-dimensional object recognition method based on a multi-view double-attention network, and the method comprises the following steps: 1, projecting an original three-dimensional object from n views to a two-dimensional plane, rendering the original three-dimensional object to obtain n views, and carrying out the feature extraction of the n views through a basic CNN model, and correspondingly obtaining n visual features; 2, inputting the n visual features into a view space attention module for processing to obtain a visual space descriptor; 3, inputting the n visual features into a view channel attention module for processing to obtain visual channel descriptors; and 4, combining the visual space descriptor and the visual channel descriptor to obtain a three-dimensional shape descriptor, and inputting the three-dimensional shape descriptor into a full-connection network to complete object identification so as to obtain a prediction identification classification result of the original three-dimensional object.

Description

technical field [0001] The invention relates to a three-dimensional object recognition method, in particular to a three-dimensional object recognition method based on a multi-view double attention network. Background technique [0002] In recent years, with the development of 3D imaging sensors and 3D reconstruction technology, people can easily capture a large amount of 3D object structure information from daily life. The recognition of 3D objects has become one of the most fundamental problems in the fields of computer vision and artificial intelligence. With the rapid development of large-scale 3D databases and deep learning, various methods have been proposed for 3D object recognition. 3D object recognition research is mainly divided into two categories according to different methods: early traditional methods and recent deep learning methods. Early 3D object recognition generally uses artificially designed 3D data description features and machine learning methods for ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/64G06V10/462G06N3/048G06F18/213G06F18/2415
Inventor 蔡宇王文举王涛
Owner UNIV OF SHANGHAI FOR SCI & TECH
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