scholarly journals Computer Graphics. Shape-Similarity Search of 3D Models by Using Moment Envelopes.

Author(s):  
Tomo Otagiri ◽  
Masatoshi Ibato ◽  
Tsuyoshi Takei ◽  
Ryutarou Ohbuchi
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.


2005 ◽  
Vol 23 (2/3/4) ◽  
pp. 70 ◽  
Author(s):  
Ryutarou Ohbuchi ◽  
Takahiro Minamitani ◽  
Tsuyoshi Takei

2014 ◽  
Vol 54 (4) ◽  
pp. 1036-1049 ◽  
Author(s):  
Adrián Kalászi ◽  
Dániel Szisz ◽  
Gábor Imre ◽  
Tímea Polgár

1998 ◽  
Vol 10 (6) ◽  
pp. 996-1004 ◽  
Author(s):  
M. Ankerst ◽  
H.-P. Kriegel ◽  
T. Seidl

2016 ◽  
Vol 110 (3) ◽  
pp. 157a
Author(s):  
Takeshi Kawabata ◽  
Hirofumi Suzuki ◽  
Haruki Nakamura

2019 ◽  
Vol 26 ◽  
pp. 29-35
Author(s):  
I.A. TREGUBOVA ◽  

Progress in hardware and software development is impressively fast. The main reason of computer graphics fast improvement is a full experience that can be reached though visual representation of our world. Therefore, the most interesting problem of it is a realistic image with high quality and resolution, which often requires procedural graphics generation. The article analyzes simplicity of a fractal and mathematics abstraction. Mathematics describes not only accuracy and logic but also beauty of the Universe. Mountains, clouds, trees, cells do not fit into the world of Euclidean geometry. They cannot be described by its methods. But fractals and fractal geometry solve that problem. Fractals are fairly simple equations on a sheet of paper with bright, unusual images, and, above all, they explain things. Fractal is a figure in the space, which consists of statistical character as the whole. It is self-similar, and therefore looks ‘roughly’ same and does not depend on its scale. So, any complex object can be called a fractal, if it has the same shape, as the parts it consists of. Fractal is abstract, and it helps to translate any algebraic problem into geometric, where solution is always obvious. A lot of researches in the field of fractal graphics has been carried out, but there are still issues that deserve considerable attention and more perfect solutions. The main purpose of the work is codes development with object-oriented programming languages for fractal graphics rendering. The article analyzes simplicity of a fractal and mathematics abstraction. Procedural generation was described as a method of algorithmic data generation for 3D models and textures creation. Code was written with general-purpose programming language Python, which renders step by step creation of fractal composition and variations of fractal images. Fractal generation used for modeling is part of realism in computer graphics In summary, procedural generation is very important for video games, as it can be used to automatically create large amount of game content. The random generation of natural looking landscapes is based on geometric computer generated images Created compositions can be used in computer science for image compression, in medicine for the study of the cellular level of organs, etc.


2003 ◽  
Vol 12 (01) ◽  
pp. 37-56 ◽  
Author(s):  
JEONG-JUN SONG ◽  
FOROUZAN GOLSHANI

We introduce two complementary feature extraction methods for shape similarity based retrieval of 3D object models. The proposed methods lead us to achieve effectiveness and robustness in searching similar 3D models, and eventually support two essential query modes, namely, query by 3D model and query by 2D image. Our feature extraction scheme is inspired by the observation of human behavior in recognizing 3D objects. The process of extracting spatial arrangement from a 3D object can be considered as using human tactile sensation without visual information. On the other hand, the process of extracting 2D features from multiple views can be considered as examining an object by moving the viewing points (or camera positions). We propose a hybrid method of 3D model identification by object-centered feature extraction, which utilizes the Extended Gaussian Image (EGI) surface normal distribution and distance distributions between object surface points and origin. Another technique need in parallel is a hybrid method using view-centered features, which adopts simple geometric attributes such as circularity, rectangularity and eccentricity. To generate a signature for view-centered features, we have measured distances of a feature between different views and constructing histogram of the distance. We also address the fundamental problem of obtaining sample points on an object surface, which is important to extract reliable features from the object model.


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