Geometric Algorithms

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课程主页: https://www.coursera.org/archive/geometric-algorithms

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课程大纲

Plane Sweep Algorithms
Voronoi diagrams and Delaunay triangulations
Orthogonal range searching

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Course Information: In many areas of computer science such as robotics, computer graphics, virtual reality, and geographic information systems, it is necessary to store, analyze, and create or manipulate spatial data. This course deals with the algorithmic aspects of these tasks: we study techniques and concepts needed for the design and analysis of geometric algorithms and data structures. Each technique and concept will be illustrated on the basis of a problem arising in one of the application areas mentioned above. Goals: At the end of this course participants should be able - to decide which algorithm or data structure to use in order to solve a given basic geometric problem, - to analyze new problems and come up with their own efficient solutions using concepts and techniques from the course. Prerequisites: In order to successfully take this course, you should already have a basic knowledge of algorithms and mathematics. Here's a short list of what you are supposed to know: - O-notation, Ω-notation, Θ-notation; how to analyze algorithms - Basic calculus: manipulating summations, solving recurrences, working with logarithms, etc. - Basic probability theory: events, probability distributions, random variables, expected values etc. - Basic data structures: linked lists, binary search trees, etc. - Graph terminology - Programming skills for practical assignments Most of the material in this course is based on the following book: M. de Berg, O. Cheong, M. van Kreveld, and M. Overmars. Computational Geometry: Algorithms and Applications (3rd edition). Springer-Verlag, 2008. It is not mandatory to buy this book. However if participants want to know more than is offered in this course or want to have another look at the material discussed in the lectures, we recommend buying this book. The video lectures contain a few very minor mistakes. A list of these mistakes can be found under resources. If you think you found an error, report a problem by clicking the square flag at the bottom of the lecture or quiz where you found the error.

几何算法:课程信息:在计算机科学的许多领域,例如机器人技术,计算机图形学,虚拟现实和地理信息系统,必须存储,分析,创建或操纵空间数据。本课程涉及这些任务的算法方面:我们研究设计和分析几何算法和数据结构所需的技术和概念。将基于在上述应用领域之一中出现的问题来说明每种技术和概念。 目标: 在本课程结束时,参与者应该能够 -决定使用哪种算法或数据结构来解决给定的基本几何问题, -使用课程中的概念和技术分析新问题并提出自己的有效解决方案。 先决条件: 为了成功上这门课程,您应该已经具有算法和数学的基础知识。这是您应该了解的简短列表: -O符号,Ω符号,Θ符号;如何分析算法 -基本演算:处理求和,求解递归,使用对数等。 -基本概率论:事件,概率分布,随机变量,期望值等 -基本数据结构:链表,二进制搜索树等。 -图形术语 -实际作业的编程技巧 本课程中的大多数材料都是基于以下书籍: M. de Berg,O。Cheong,M。van Kreveld和M. Overmars。计算几何:算法与应用(第3版)。施普林格出版社,2008年。 买这本书不是强制性的。但是,如果参与者想了解本课程所提供的知识以外的其他知识,或者想再次看一下讲座中讨论的材料,我们建议您购买本书。 视频讲座包含一些非常小的错误。在资源下可以找到这些错误的列表。如果您认为发现错误,请通过单击讲座或测验底部找到错误的方形标记来报告问题。

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