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Object extraction method and device

An object extraction and object technology, applied in the computer field, can solve problems such as poor accuracy

Pending Publication Date: 2022-05-13
NAVINFO
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides an object extraction method and device to overcome the problem of poor accuracy of object extraction

Method used

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  • Object extraction method and device

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Embodiment Construction

[0093] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of this application.

[0094] combine first figure 1 Introduce the convolutional neural network involved in this application, figure 1 Schematic diagram of the network structure of the convolutional neural network provided in the embodiment of this application:

[0095] Convolutional Neural Network: Convolutional Neural Networks (CNN) is a type of feedforward neural network that ...

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Abstract

The embodiment of the invention provides an object extraction method and device, and the method comprises the steps: inputting a first picture comprising at least one object into a semantic segmentation feature network, so as to enable the semantic segmentation feature network to output a first feature map. The first feature graph is processed according to the semantic segmentation classification network, a semantic segmentation result graph is obtained, and the semantic segmentation result graph comprises a graph layer of the object mask graph and a graph layer of the background mask graph. And processing the layers of the first feature graph and the object mask graph according to the interest point generation network to obtain at least one interest point. And processing the first feature map and the at least one interest point according to the interest point control network and the instance selection network to obtain a target mask map corresponding to the at least one interest point. And respectively determining the position of each object in the first picture according to the target mask graph corresponding to the at least one interest point so as to extract at least one object. According to the embodiment of the invention, the effect and accuracy of extracting the rod-shaped object are effectively ensured.

Description

technical field [0001] The embodiments of the present application relate to computer technology, and in particular to an object extraction method and device. Background technique [0002] In the process of map construction, it is usually necessary to extract pole-shaped objects in image information, such as lampposts, utility poles, etc. [0003] At present, when the relevant technology extracts the rod-shaped object in the image information, it can first detect the boundary of the bounding box of a single object in the image, and then use the segmentation method to complete the semantic segmentation of the foreground and background, and finally combine the single object The boundary of the bounding box of the target and the result of the semantic segmentation of the foreground and background to realize the extraction of each rod in the image. [0004] However, since the shape of the rod object is elongated, the aspect ratio and size of the bounding box are unbalanced, so t...

Claims

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Application Information

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IPC IPC(8): G06V10/44G06V10/28G06V10/82G06V10/26G06V10/25G06V10/774G06V10/764G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06N3/045G06F18/241G06F18/214
Inventor 黄伟杰田文善康勇
Owner NAVINFO
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