Point cloud completion method based on visual angle generator

A generator and perspective technology, applied in the field of computer vision, can solve problems such as insufficient performance, achieve the effect of excellent completion and improve the quality of completion

Pending Publication Date: 2022-04-05
SOUTHEAST UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The coarse-to-fine strategy is suitable for the cloud completion task of residual defects caused by resolution, and does not perform well enough for the defects caused by perspective occlusion

Method used

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  • Point cloud completion method based on visual angle generator
  • Point cloud completion method based on visual angle generator
  • Point cloud completion method based on visual angle generator

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Embodiment Construction

[0044] The present invention will be further clarified below with reference to the accompanying drawings and specific embodiments. It should be understood that the following specific embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. It should be noted that the words "front", "rear", "left", "right", "upper" and "lower" used in the following description refer to the directions in the drawings, and the words "inner" and "outer" ” refer to directions towards or away from the geometric center of a particular part, respectively.

[0045] The point cloud completion methods based on the perspective generator in this embodiment, the algorithm flow chart is as follows figure 1 shown. Specifically include the following steps:

[0046] Step 1: Data set generation: use the invisible point removal algorithm to process the data set to generate the residual defect cloud P v , including three modules: perspective selection, s...

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Abstract

The invention discloses a point cloud completion method based on a visual angle generator. The method comprises the following steps: firstly, preprocessing a data set by using an invisible point removal algorithm; secondly, designing a point cloud complementation network PV-Net based on a visual angle, wherein the network comprises an encoder E and a decoder D; wherein the encoder E is responsible for extracting a global feature f of an input incomplete point cloud, the decoder D is responsible for decoding the global feature f to obtain a complete point cloud, and the decoder adopts a visual angle-based strategy from part to whole and is realized through the visual angle generator. According to the point cloud completion method provided by the invention, an intermediate point cloud under an adjacent view angle is generated by fully utilizing view angle correlation between incomplete point clouds; the incomplete degree of the incomplete point cloud is gradually reduced by expanding the visual angle of the incomplete point cloud, so that the complete shape of the incomplete point cloud is deduced better, mutual supervision is performed by using the incomplete point cloud, a decoder is promoted to pay better attention to local details, and a better completion effect is achieved.

Description

technical field [0001] The invention belongs to the technical field of computer vision; in particular, it relates to a point cloud completion technology based on a viewing angle generator. Background technique [0002] In recent years, point cloud completion tasks have attracted extensive attention in the fields of computer vision and robotics. Raw point cloud data acquired by devices such as depth cameras or lidars are often sparse and incomplete due to limitations such as resolution or occlusion. Incomplete 3D objects greatly limit its application in real life, such as object detection, scene segmentation and other downstream tasks. Therefore, it is very necessary to predict or infer the missing structure from the partially observed residual defect cloud, which has very important potential and value in the field of 3D vision, especially in application scenarios such as autonomous driving and robotics. [0003] Many works have attempted to solve the point cloud completion...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06N3/04
CPCY04S10/50
Inventor 达飞鹏张子煜
Owner SOUTHEAST UNIV
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