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Multi-view 3D Model Retrieval Method Based on Block Convolutional Neural Network

A convolutional neural network and three-dimensional model technology, which is applied in the field of multi-view three-dimensional model retrieval based on block convolutional neural network, can solve the problems of large amount of calculation, unsatisfactory effect, and restrict the development of traditional methods, and achieve the effect of excellent performance.

Active Publication Date: 2022-05-13
SHANDONG ARTIFICIAL INTELLIGENCE INST +1
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AI Technical Summary

Problems solved by technology

However, in practical applications, using traditional methods for rendering and feature extraction of 3D models is not only computationally intensive but also unsatisfactory.
These difficulties limit the development of related traditional methods

Method used

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  • Multi-view 3D Model Retrieval Method Based on Block Convolutional Neural Network

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Embodiment Construction

[0025] Attached below figure 1 The present invention will be further described.

[0026] A multi-view 3D model retrieval method based on block convolutional neural network, comprising:

[0027] a) Rendering the 3D model to obtain N 2D views of the 3D model. The three-dimensional model may be a three-dimensional model generated by a computer, and the computer renders the three-dimensional model to obtain multiple two-dimensional views. The 3D model can also be a real-world object, and X cameras with different angles are set around the object to obtain two-dimensional views of the object at different angles. Preferably, a camera is set every 30 degrees in the circumferential direction around the object, and 12 two-dimensional views are obtained by setting 12 cameras.

[0028] b) The previous multi-view method directly inputs the obtained multiple views into the weight-shared convolutional neural network at the same time to obtain the view features of each view. In this metho...

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Abstract

A multi-view 3D model retrieval method based on block convolutional neural network, through multi-view images, using block convolution layer to mine the internal relationship between views in the process of extracting view features. According to the cosine similarity between each view feature and the feature after maximum view pooling, different weights are assigned to each view, and the distinction between view features is used to obtain more discriminative model features. When generating the loss function, not only the model features but also the view features are considered, which can better constrain the network for learning. This multi-view 3D model retrieval method based on block convolutional neural network achieves excellent performance in related 3D model retrieval datasets.

Description

technical field [0001] The invention relates to the field of three-dimensional vision, in particular to a multi-view three-dimensional model retrieval method based on a block convolutional neural network. Background technique [0002] With the development of 3D representation technology and computer hardware performance, 3D vision has attracted more and more attention from researchers. Compared with traditional two-dimensional images, three-dimensional vision is a more realistic description of the real world, including the spatial structure information of three-dimensional objects and the characteristics of three-dimensional geometry and contour curves. 3D model retrieval is a research hotspot in the field of 3D vision. Related research methods can be divided into two stages (1) 3D model retrieval methods based on traditional methods, and (2) 3D model retrieval methods based on deep learning. [0003] The 3D model retrieval method based on the traditional method is to gene...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/04G06F16/53
CPCG06F16/53G06N3/045G06F18/213G06F18/24147G06F18/253G06F18/214
Inventor 高赞邵煜翔程志勇陈达舒明雷聂礼强
Owner SHANDONG ARTIFICIAL INTELLIGENCE INST
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