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Model optimization method and related device, electronic equipment and storage medium

An optimization method and model technology, applied in the field of computer vision, can solve problems such as complex solution process, loss of details in network construction algorithm, etc., to achieve the effect of improving quality and efficiency, reducing algorithm overhead, and improving optimization quality

Active Publication Date: 2021-11-26
SHENZHEN TETRAS AI TECH CO LTD
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  • Claims
  • Application Information

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Problems solved by technology

[0003] At present, the existing detail optimization methods usually choose to optimize the indirect representation of 3D models such as Truncated Signed Distance Function (TSDF). On the 3D model of , not only introduces additional algorithm overhead, but also the network construction algorithm itself may lose some details again

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  • Model optimization method and related device, electronic equipment and storage medium
  • Model optimization method and related device, electronic equipment and storage medium
  • Model optimization method and related device, electronic equipment and storage medium

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Embodiment Construction

[0040] The solutions of the embodiments of the present application will be described in detail below in conjunction with the accompanying drawings.

[0041] In the following description, for purposes of illustration rather than limitation, specific details, such as specific system architectures, interfaces, and techniques, are set forth in order to provide a thorough understanding of the present application.

[0042] The terms "system" and "network" are often used interchangeably herein. The term "and / or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist simultaneously, and there exists alone B these three situations. In addition, the character " / " in this article generally indicates that the contextual objects are an "or" relationship. In addition, "many" herein means two or more than two.

[0043] see figure 1 , figure 1 is ...

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Abstract

The invention discloses a model optimization method, a related device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a to-be-optimized model; wherein the to-be-optimized model comprises a plurality of model patches, and the model patches are composed of model vertexes; obtaining attribute information and first normal information of each model patch, and obtaining first position information of each model vertex; optimizing the first normal information based on the attribute information to obtain second normal information; and optimizing the first position information based on the first normal information and the second normal information to obtain second position information of the model vertex so as to optimize the to-be-optimized model. According to the scheme, the model optimization quality and efficiency can be improved.

Description

technical field [0001] The present application relates to the technical field of computer vision, in particular to a model optimization method and related devices, electronic equipment and storage media. Background technique [0002] In 3D reconstruction applications, due to software-level reasons such as reconstruction algorithms, or hardware-level reasons such as sensor accuracy, the final reconstruction model often lacks a lot of geometric details. Therefore, it is necessary to optimize the details of the reconstructed model to improve the quality of the model. [0003] At present, the existing detail optimization methods usually choose to optimize the indirect representation of 3D models such as Truncated Signed Distance Function (TSDF). On the 3D model of the network, it not only introduces additional algorithm overhead, but also the network construction algorithm itself may lose some details again. In view of this, how to improve the quality and efficiency of model o...

Claims

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Application Information

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IPC IPC(8): G06T5/50G06T7/50G06T7/80G06T7/90G06T17/00
CPCG06T7/50G06T7/85G06T7/90G06T5/50G06T17/00
Inventor 李辰宸项骁骏余亦豪
Owner SHENZHEN TETRAS AI TECH CO LTD
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