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Free viewpoint 3D model reconstruction method of single frame image based on deep learning

A 3D model and deep learning technology, applied in image data processing, 3D modeling, instruments, etc., can solve the problems of single camera viewpoint, lack of variability, and flexible change of 3D models, achieving powerful functions, reducing operation difficulty, The effect of improving efficiency

Active Publication Date: 2021-02-12
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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AI Technical Summary

Problems solved by technology

However, many current studies always combine the learning of 3D model shape and viewpoint. The generated 3D model is only suitable for a single camera viewpoint, lacks certain variability, and cannot be flexibly changed following viewpoint changes, which is relatively limited in practical applications.

Method used

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  • Free viewpoint 3D model reconstruction method of single frame image based on deep learning
  • Free viewpoint 3D model reconstruction method of single frame image based on deep learning
  • Free viewpoint 3D model reconstruction method of single frame image based on deep learning

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Embodiment Construction

[0054] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. The present invention decouples viewpoint-independent three-dimensional model reconstruction and camera viewpoint estimation tasks in three-dimensional reconstruction through deep learning neural network. On the one hand, the viewpoint-independent 3D model does not change with the change of the camera viewpoint, and has significant mobility and adaptability; on the other hand, a free viewpoint can be derived from the estimated camera viewpoint, and multiplied by the viewpoint-independent 3D model, we get Viewpoint-free 3D models expand the scope of use of the method.

[0055] It is worth noting that the decoupling of the neural network in the present invention does not take any compulsory measures, but is guided by the physical calculation of the free-viewpoint 3D model jointly generated by the view-point-independent model and the free-...

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Abstract

The invention discloses a method for reconstructing a three-dimensional model of a single-frame image free from viewpoint based on deep learning, comprising the following steps: generating training samples; using a feature extraction network to obtain high-level semantics of pictures; decoupling image semantics into an output viewpoint through a decoupling network Independent 3D model point cloud and camera viewpoint parameters; viewpoint-independent 3D model reconstruction; camera viewpoint estimation and free viewpoint generation; free viewpoint 3D model generation; and deep learning model training. The method of the invention can simply and efficiently reconstruct a three-dimensional model of a free viewpoint from a single frame image, improves the generalization of the model, and broadens the application range.

Description

technical field [0001] The present invention relates to the field of three-dimensional model reconstruction, in particular to a method for reconstructing a three-dimensional model from a free viewpoint of a single frame image based on deep learning. Background technique [0002] The free-viewpoint 3D model is based on the ordinary 3D model, allowing people to have the same stereoscopic feeling when switching viewing angles, which can provide a more realistic and natural visual environment for stereoscopic multimedia. Due to the complexity of the 3D model itself, the cost of generating a free-viewpoint 3D model by traditional methods is high, requiring workers to manually render and generate more 3D models from different viewpoints, which is inefficient and complicated to operate. How to generate a free-viewpoint 3D model simply and efficiently has always been a research hotspot for researchers, and has great application potential. [0003] The viewpoint-independent 3D model...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T17/00G06F30/27G06F30/10
CPCG06T17/00G06F30/20
Inventor 杨路李佑华杨经纶
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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