Progress and Review of 3D Image Feature Reconstruction

Considering the problems of poor effect, long reconstruction time, large mean square error (MSE), low signal-to-noise ratio (SNR), and structural similarity index (SSIM) of traditional methods in three-dimensional (3D) image virtual reconstruction, the effect of 3D image virtual reconstruction based on visual communication is proposed. Using the distribution set of 3D image visual communication feature points, the feature point components of 3D image virtual reconstruction are obtained. By iterating the 3D image visual communication information, the features of 3D image virtual reconstruction in visual communication are decomposed, and the 3D image visual communication model is constructed. Based on the calculation of the difference of 3D image texture feature points, the spatial position relationship of 3D image feature points after virtual reconstruction is calculated to complete the texture mapping of 3D image. The deep texture feature points of 3D image are extracted. According to the description coefficient of 3D image virtual reconstruction in visual communication, the virtual reconstruction results of 3D image are constrained. The virtual reconstruction algorithm of 3D image is designed to realize the virtual reconstruction of 3D image. The results show that when the number of samples is 200, the virtual reconstruction time of this paper method is 2.1 s, and the system running time is 5 s; the SNR of the virtual reconstruction is 35.5 db. The MSE of 3D image virtual reconstruction is 3%, and the SSIM of virtual reconstruction is 1.38%, which shows that this paper method can effectively improve the ability of 3D image virtual reconstruction.

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Measurement and classification of shanghai female face shape based on 3D image feature

2010 3rd International Congress on Image and Signal Processing ◽

10.1109/cisp.2010.5648207 ◽

2010 ◽

Cited By ~ 2

Author(s):

Yanqiu Xu ◽

Jianxin Qiu ◽

Ling Ma

Keyword(s):

Image Feature ◽

3D Image ◽

Face Shape

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Enhanced Switch Image-Based Visual Servoing Dealing with FeaturesLoss

Electronics ◽

10.3390/electronics8080903 ◽

2019 ◽

Vol 8 (8) ◽

pp. 903 ◽

Cited By ~ 2

Author(s):

Ahmad Ghasemi ◽

Pengcheng Li ◽

Wen-Fang Xie ◽

Wei Tian

Keyword(s):

Visual Servoing ◽

Experimental Tests ◽

Reconstruction Algorithm ◽

Response Speed ◽

Image Features ◽

Image Feature ◽

System Response ◽

Switch Control ◽

Six Degree Of Freedom ◽

Feature Reconstruction

In this paper, an enhanced switch image-based visual servoing controller for a six-degree-of-freedom (DOF) robot with a monocular eye-in-hand camera configuration is presented. The switch control algorithm separates the rotating and translational camera motions and divides the image-based visual servoing (IBVS) control into three distinct stages with different gains. In the proposed method, an image feature reconstruction algorithm based on the Kalman filter is proposed to handle the situation where the image features go outside the camera’s field of view (FOV). The combination of the switch controller and the feature reconstruction algorithm improves the system response speed and tracking performance of IBVS, while ensuring the success of servoing in the case of the feature loss. Extensive simulation and experimental tests are carried out on a 6-DOF robot to verify the effectiveness of the proposed method.

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On 2D-3D Image Feature Detections for Image-To-Geometry Registration in Virtual Dental Model

2020 IEEE International Conference on Visual Communications and Image Processing (VCIP) ◽

10.1109/vcip49819.2020.9301774 ◽

2020 ◽

Author(s):

Hui Tang ◽

Tai-Chiu Hsung ◽

Walter Y.H. Lam ◽

Leo Y. Y. Cheng ◽

Edmond H.N. Pow

Keyword(s):

Image Feature ◽

3D Image ◽

Dental Model

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The tracking study of 3D image feature points of aerobic movements of high difficulty

The Imaging Science Journal ◽

10.1080/13682199.2017.1401689 ◽

2017 ◽

Vol 66 (4) ◽

pp. 211-219

Author(s):

Xiao-hui Shi

Keyword(s):

Image Feature ◽

Feature Points ◽

3D Image

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High-resolution electron microscopy of the atomic structure of some grain boundaries in Au

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100143663 ◽

1986 ◽

Vol 44 ◽

pp. 414-415

Author(s):

W. Krakow ◽

D. A. Smith

Keyword(s):

Atomic Structure ◽

High Resolution Electron Microscopy ◽

Image Features ◽

Image Feature ◽

Resolution Electron ◽

Tilt Boundaries ◽

Processing Techniques ◽

Atom Position ◽

Structure Configuration

The successful determination of the atomic structure of [110] tilt boundaries in Au stems from the investigation of microscope performance at intermediate accelerating voltages (200 and 400kV) as well as a detailed understanding of how grain boundary image features depend on dynamical diffraction processes variation with specimen and beam orientations. This success is also facilitated by improving image quality by digital image processing techniques to the point where a structure image is obtained and each atom position is represented by a resolved image feature. Figure 1 shows an example of a low angle (∼10°) Σ = 129/[110] tilt boundary in a ∼250Å Au film, taken under tilted beam brightfield imaging conditions, to illustrate the steps necessary to obtain the atomic structure configuration from the image. The original image of Fig. 1a shows the regular arrangement of strain-field images associated with the cores of ½ [10] primary dislocations which are separated by ∼15Å.

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