3D Skeleton Construction by Multi-view 2D Images and 3D Model Segmentation

Author(s):  
Shih-Ming Chang ◽  
Yi-Sheng Tsai ◽  
Hui-Huang Hsu ◽  
Kuan-Ching Li
Author(s):  
Joseph C. Tsai ◽  
Shih Ming Chang ◽  
Shwu Huey Yen ◽  
Timothy K. Shih ◽  
Kuan Ching Li

2021 ◽  
Vol 29 ◽  
pp. 133-140
Author(s):  
Bin Liu ◽  
Shujun Liu ◽  
Guanning Shang ◽  
Yanjie Chen ◽  
Qifeng Wang ◽  
...  

BACKGROUND: There is a great demand for the extraction of organ models from three-dimensional (3D) medical images in clinical medicine diagnosis and treatment. OBJECTIVE: We aimed to aid doctors in seeing the real shape of human organs more clearly and vividly. METHODS: The method uses the minimum eigenvectors of Laplacian matrix to automatically calculate a group of basic matting components that can properly define the volume image. These matting components can then be used to build foreground images with the help of a few user marks. RESULTS: We propose a direct 3D model segmentation method for volume images. This is a process of extracting foreground objects from volume images and estimating the opacity of the voxels covered by the objects. CONCLUSIONS: The results of segmentation experiments on different parts of human body prove the applicability of this method.


2015 ◽  
Vol 74 (6) ◽  
Author(s):  
Siti Syazalina Mohd. Sobani ◽  
Nasrul Humaimi Mahmood ◽  
Nor Aini Zakaria ◽  
Ismail Ariffin

This paper presents a simple computation method to reconstruct 3-dimensional (3D) model from a sequence of 2-dimensional (2D) images using a multiple-view camera setup. The 3D model is acquired by applying several images processing on few 2D images captured by digital camera with different angle of views. The setup for this study consisted of a digital camera mounted on a tripod stand focusing at a block of model object on a turntable with black floor and background. 36 different angles are used to capture the images where every view angle differs by ten degree (10°) with another view in a fixed sequence. The image processing applied on all 2D images to be reconstructed as 3D surface are image segmentation, Radon transform (RT), image filtering, morphological operation, edge detection, and boundary extraction. The results for 3D model reconstruction shows it is well reconstructed, with a smooth texture obtained using 3D mesh and Delaunay triangulation, while the shape is nearly identical to the original model while the remaining are distinguishable.  


Author(s):  
Y. Wang ◽  
R. Liu ◽  
S. Endo ◽  
Y. Uehara

2014 ◽  
Vol 1049-1050 ◽  
pp. 1417-1420
Author(s):  
Hui Jia ◽  
Guo Hua Geng ◽  
Jian Gang Zhang

3D model segmentation is a new research focus in the field of computer graphics. The segmentation algorithm of this paper is consistent segmentation which is about a group of 3D model with shape similarity. A volume-based shape-function called the shape diameter function (SDF) is used to on behalf of the characteristics of the model. Gaussian mixture model (GMM) is fitting k Gaussians to the SDF values, and EM algorithm is used to segment 3D models consistently. The experimental results show that this algorithm can effectively segment the 3D models consistently.


2008 ◽  
Vol E91-D (4) ◽  
pp. 1149-1158 ◽  
Author(s):  
B. ZHENG ◽  
J. TAKAMATSU ◽  
K. IKEUCHI

Author(s):  
Mohamed AbdElAziz ◽  
Mohamed Ayman ◽  
Mohamed Osama ◽  
Tarek Medhat ◽  
Hager Sobeah ◽  
...  

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