Variational mechanism-based indoor scene three-dimensional reconstruction method

An indoor environment and 3D reconstruction technology, which is applied to the reconstruction of large-scale indoor scenes and the field of 3D reconstruction of indoor environment, to achieve the effect of reducing the amount of processed data, improving reconstruction accuracy, and reducing computational complexity

Inactive Publication Date: 2013-08-14
BEIJING UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Effectively solve the cost and real-time problems of the 3D reconstruction algorithm, and improve the reconstruction accuracy

Method used

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  • Variational mechanism-based indoor scene three-dimensional reconstruction method
  • Variational mechanism-based indoor scene three-dimensional reconstruction method
  • Variational mechanism-based indoor scene three-dimensional reconstruction method

Examples

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Embodiment Construction

[0104] figure 1 It is a flow chart of an indoor 3D scene reconstruction method based on a variational model, including the following steps:

[0105] Step 1, obtain the calibration parameters of the camera, and establish a distortion correction model.

[0106] Step 2, establish camera pose description and camera projection model.

[0107] Step 3, use the SFM-based monocular SLAM algorithm to realize camera pose estimation.

[0108] Step 4: Establish a variational mechanism-based depth map estimation model and solve the model.

[0109] Step five, establishing a key frame selection mechanism to realize updating of the 3D scene.

[0110] An application example of the present invention is given below.

[0111]The RGB camera used in this example is Point Gray Flea2, the image resolution is 640×480, the maximum frame rate is 30fps, the horizontal field of view is 65°, and the focal length is about 3.5mm. The PC used is equipped with GTS450GPU and i5 quad-core CPU.

[0112] Dur...

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Abstract

The invention belongs to crossing field of computer vision and intelligent robots and discloses a variational mechanism-based large-area indoor scene reconstruction method. The method comprises the following steps: step 1, acquiring calibration parameters of a camera, and building an aberration correcting model; step 2, building a camera position and gesture depiction and camera projection model; step 3, utilizing an SFM-based monocular SFM (Space Frequency Modulation) algorithm to realize camera position and gesture estimation; step 4, building a variational mechanism-based depth map estimation model, and performing solving on the model; and step 5, building a key frame selection mechanism to realize three-dimensional scene renewal. According to the invention, an RGB (Red Green Blue) camera is adopted to acquire environmental data, and a variational mechanism-based depth map generation method is proposed through utilizing a high-precision monocular positioning algorithm, so that quick large-area indoor three-dimensional scene reconstruction is realized, and problems of three-dimensional reconstruction algorithm cost and real-time performance are effectively solved.

Description

technical field [0001] The invention belongs to the intersecting field of computer vision and intelligent robots, relates to a three-dimensional reconstruction technology of an indoor environment, and in particular relates to a reconstruction method of a large-scale indoor scene based on a variational mechanism. technical background [0002] With the continuous deepening of Simultaneous Localization And Mapping (SLAM) research, three-dimensional modeling of the environment has gradually become a research hotspot in this field, attracting the attention of many scholars. G. Klein et al first proposed the concept of Parallel Tracking and Mapping (PTAM) in the field of augmented reality (AR) in 2007 to solve the problem of real-time modeling of the environment. PTAM divides camera tracking and map generation into two independent threads, uses the FastCorner method to update the detection feature points, and uses the optimal local and global beam adjustment method (Bundle Adjustm...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/00G06T7/00
Inventor 贾松敏王可李雨晨李秀智
Owner BEIJING UNIV OF TECH
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