Solid Modelling Data Structures For Computer Vision

2005 ◽  
Author(s):  
J.J. Pfeiffer ◽  
C.A. Soderlund
Keyword(s):  
Computer Vision ◽  
Data Structures ◽  
Solid Modelling ◽  
Modelling Data

Modelling Data Structures

2021 ◽  
pp. 57-66
Author(s):  
Ludwik Czaja
Keyword(s):  
Data Structures ◽  
Modelling Data

scholarly journals Graph Cuts, Caveat Utilitor, and Euler's Bridges of Konigsberg

2008 ◽  
Author(s):  
Nicholas J. Tustison ◽  
Paul Yushkevich ◽  
Zhuang Song ◽  
James Gee
Keyword(s):  
Computer Vision ◽  
Data Structures ◽  
Energy Minimization ◽  
Research Use ◽  
General Requirement ◽  
Energy Functions ◽  
Philosophical Inquiry ◽  
Related Data ◽  
Markov Random ◽  
The Subject

Graph-based algorithms have enjoyed renewed interest for solving computer vision problems. These algorithms have been the subject of intense interest and research. In order to maintain the ITK library au courant, we developed a framework for graph-based methods of energy minimization in ITK which employ energy functions derived within a Markov Random Field (MRF) context. This required not only the implementation of the energy minimization methodology but also the more general requirement of introducing graph-related data structures into ITK which can be used for other graph-based algorithms pertinent to future extensions of the ITK library.Please note that some of the algorithms described in this paper may be covered by patents and, as such, it is incumbent upon the user to seek licenses before building the binaries which utilize this code. Also note that “research use” is not exempt from acquiring such licenses. The only exemption from patent restrictions is “. . . amusement, to satisfy idle curiosity, or for strictly philosophical inquiry.”

Human Vision and Computer Vision

1985 ◽  
Vol 30 (1) ◽  
pp. 47-47
Author(s):  
Herman Bouma
Keyword(s):  
Computer Vision ◽  
Human Vision

Computer vision for industrial applications

1983 ◽  
Vol 2 (5) ◽  
pp. 130
Author(s):  
J.A. Losty ◽  
P.R. Watkins
Keyword(s):  
Computer Vision ◽  
Industrial Applications

Specification scheme for the visualisation of data structures

1994 ◽  
Vol 9 (3) ◽  
pp. 127
Author(s):  
X.-B. Lu ◽  
F. Stetter
Keyword(s):  
Data Structures

The machine training in problems of satellite images’s processing

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Computer Vision ◽  
Satellite Images ◽  
Vision Systems ◽  
Earth Remote Sensing ◽  
Practical Applications ◽  
Convolution Neural Networks ◽  
Computer Vision Systems ◽  
Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

Sign in / Sign up

Export Citation Format

Share Document