生成单调多面体的视觉识别视图模型。博士论文成果展示

A. Salamończyk, W. Mokrzycki
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引用次数: 0

摘要

本文的主要研究成果是:利用视角球的视角投影思想,开发合适的方法和算法,以获得物体的完整视图表示,比较和选择最佳算法,并展示如何将观察模型与从距离图像中提取的物体进行匹配。证明了用复杂度为O(n2)的算法可以得到单调多面体的近似视图表示,并且给出了与距离图像数据匹配单调多面体的最小视图表示数为O(n2)。针对视觉识别系统中单调多面体视图表示的生成方法进行了研究,并给出了其中的一些方法。视图表示用于许多领域,包括识别任务,例如作为自动化和机器人中的视觉通道元素。对象的三维视图表示可以离线构建并保存在数据库中,以便在识别任务中进一步使用。
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Generating view models of monotone polyhedrons for visual identification. Presentation of results of the PhD thesis
Main results the PhD dissertation are presented in which the goals were: to develop appropriate methods and algorithms in order to obtain a complete view representation of the object using the idea of the viewing sphere with the perspective projection, to compare and select the best algorithm for this task, and to show how the viewing models can be matched with objects extracted from range images. It was proved that it is possible to obtain the approximate view representation of a monotone polyhedron using the algorithm with the complexity of O(n2) and that the minimum number of matching view representations of a monotone polyhedron given with the data from range images is O(n2). The methods of generating view representations of monotone polyhedrons are investigated for the purpose of visual recognition systems and some of them are presented. View representations are used in many areas including identification tasks, e.g. as an element of visual channel in automation and robotics. The 3D view representation of objects can be constructed offline and saved in a database for further use in the recognition task.
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来源期刊
Machine Graphics and Vision
Machine Graphics and Vision Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
0.40
自引率
0.00%
发文量
1
期刊介绍: Machine GRAPHICS & VISION (MGV) is a refereed international journal, published quarterly, providing a scientific exchange forum and an authoritative source of information in the field of, in general, pictorial information exchange between computers and their environment, including applications of visual and graphical computer systems. The journal concentrates on theoretical and computational models underlying computer generated, analysed, or otherwise processed imagery, in particular: - image processing - scene analysis, modeling, and understanding - machine vision - pattern matching and pattern recognition - image synthesis, including three-dimensional imaging and solid modeling
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