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Live-action model construction method and device taking entity target as minimum unit

A reality model and minimum unit technology, applied in the field of reality modeling, can solve the problems of high model construction cost and time-consuming, and achieve the effect of improving efficiency, low cost, and easy deployment

Active Publication Date: 2021-02-02
山东产研信息与人工智能融合研究院有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although these methods can also achieve good modeling results, the inventors found that it takes a lot of time to calculate the point cloud, and the above-mentioned real scene model construction method needs to use laser scanners, laser radars, and five-eye cameras. , depth camera and other equipment, the cost of model construction is relatively high

Method used

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  • Live-action model construction method and device taking entity target as minimum unit
  • Live-action model construction method and device taking entity target as minimum unit
  • Live-action model construction method and device taking entity target as minimum unit

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0036] refer to figure 1 , the real scene model construction method of the present embodiment with the entity target as the smallest unit, which includes:

[0037] S101: Acquire an image of a target entity in the scene, and perform instance segmentation on the target entity in the scene.

[0038] In the specific implementation, the two-dimensional color image of the scene is obtained, and the instance segmentation algorithm based on deep learning is used to realize the segmentation of the target entity.

[0039] It is understandable that the commonly used deep learning models for instance segmentation include Mask R-CNN, MaskScoring R-CNN, TensorMask, SOLO, BlendMask, YOLACT, etc. Among them, YOLACT can achieve a segmentation speed of 33FPS, which can achieve real-time effects.

[0040] In this embodiment, the YOLACT deep learning model is used to perform instance segmentation on the target entity in the scene. In this way, the result of instance segmentation can obtain the...

Embodiment 2

[0066] This embodiment provides a device for constructing a reality model with a physical object as the smallest unit, which includes:

[0067] Instance segmentation module, which is used to obtain the image of the target entity in the scene, and carry out instance segmentation to the target entity in the scene;

[0068] A model calling module, which is used to identify the category of the target entity and call the model of the target entity from the entity target database;

[0069] A coordinate transformation module, which is used to extract the key points of the target entity model and convert the pixel coordinates of the key points into three-dimensional space coordinates;

[0070] A space occupancy calculation module, which is used to calculate the position and space occupancy of the target entity based on the three-dimensional space coordinates of the key points;

[0071] The model embedding module is used to embed the target entity model into the scene model based on t...

Embodiment 3

[0081] This embodiment provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps in the method for constructing a reality model with an entity object as the smallest unit as described in the first embodiment above are realized .

[0082] This embodiment aims at the scene where the physical target model is known, by calculating the position and space occupancy information of the target entity in the scene model, to realize the fast construction of the real scene model; directly using the model of the physical target, eliminating the need for 3D point cloud reconstruction Time consumption and computational complexity can improve the efficiency of real scene model construction; at the same time, only two-dimensional images of the scene need to be collected, no other equipment is required, and the cost is low and deployment is easy.

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Abstract

The invention belongs to the field of live-action modeling, and provides a live-action model construction method and device taking an entity target as a minimum unit. The live-action model construction method taking an entity target as a minimum unit comprises the following steps: acquiring an image of a target entity in a scene, and carrying out instance segmentation on the target entity in the scene; identifying the category of the target entity and calling a model of the target entity from an entity target database; extracting key points of the target entity model, and converting the pixelcoordinates of the key points into three-dimensional space coordinates; calculating the position and space occupation of the target entity based on the three-dimensional space coordinates of the key points; based on the position and space occupation, embedding the target entity model into the scene model to realize rapid construction and updating of the live-action model.

Description

technical field [0001] The invention belongs to the field of real-scene modeling, and in particular relates to a method and device for constructing a real-scene model with a physical object as the smallest unit. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] At present, the construction of reality models has been widely used in various fields, including digital cities, smart cities, fire rescue, emergency security, earthquake prevention and disaster reduction, land resources, environmental protection, engineering and construction, manufacturing, cultural relics protection, etc. Real scene model construction can clearly show the three-dimensional state of each physical object in the current scene, and can provide more accurate and rich scene information than two-dimensional images, and provide users with faster and more convenient scene an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/00G06N3/04G06N3/08G06T7/215G06T7/73
CPCG06T17/00G06T7/215G06T7/75G06N3/08G06T2207/10028G06N3/045
Inventor 陈小忠高桢王聪袁晓颖王薇薇
Owner 山东产研信息与人工智能融合研究院有限公司