BCA608 - COMPUTATIONAL GOEMETRY
| Course Name | Code | Semester | Theory (hours/week) |
Application (hours/week) |
Credit | ECTS |
|---|---|---|---|---|---|---|
| COMPUTATIONAL GOEMETRY | BCA608 | Any Semester/Year | 3 | 0 | 3 | 7.5 |
| Prequisites | Calculus, Linear Algebra, Analytic Geometry, Data Structures, Object Oriented Programming | |||||
| Course language | Turkish | |||||
| Course type | Elective | |||||
| Mode of Delivery | Face-to-Face | |||||
| Learning and teaching strategies | Lecture Discussion Question and Answer Experiment Drill and Practice Problem Solving | |||||
| Instructor (s) | ||||||
| Course objective | Computational geometry is the study of efficient algorithms to solve geometric problems. In this course students design algorithms and analyze their efficiency in solving geometric problems. | |||||
| Learning outcomes |
| |||||
| Course Content | Analysis of Algorithms, Geometric Data Structures, Line Segment Intersection, Polygon Triangulation, Orthogonal Range Searching, Point Location | |||||
| References | ? M. J. Laszlo; Computational Geometry and Computer Graphics in C++ (1996) ? M. De Bery, M. Van Vrequeld, M. Overmars, O. Schwarzkoof; Computational Geometry (1997) | |||||
Course outline weekly
| Weeks | Topics |
|---|---|
| Week 1 | Introduction to computational geometry , typical problems in computer graphics and machine vision , algorithm complexity and robustness |
| Week 2 | Linked Lists, Lists, Stacks, Binary Search Trees, Braided Binary Search Trees, Randomized Search Trees. Quiz I |
| Week 3 | Vectors, Points, Polygons, Edges, Geometric Objects in Space, Finding the Intersection of a Line and a Triangle |
| Week 4 | Finding Star-Shaped Polygons, Finding Convex Hulls: Insertion Hull; Point Enclosure: The Ray-Shooting Method. The Signed Angle Method, Quiz II |
| Week 5 | Line Clipping: The Cyrus-Beck Algorithm; Polygon Clipping: The Sutherland-Hodgman Algorithm. |
| Week 6 | Triangulating Monotone Polygons. Quiz III |
| Week 7 | Finding Convex Hulls: Gift-Wrapping; Finding Complex Hulls: Graham Scan. |
| Week 8 | Removing Hidden Surfaces: The Depth-Sort Algorithm; Intersection of Convex Polygons. Quiz IV |
| Week 9 | Finding Delaunay Triangulations. |
| Week 10 | Finding the Intersections of Line Segments; Finding Convex Hulls: Insertion Hull , Quiz V |
| Week 11 | Contour of the Union of Rectangles; Decomposing Polygons into Monotone Pieces. |
| Week 12 | Computing the Intersection of Half-Planes; Finding the Kernel of a Polygon, Quiz VI |
| Week 13 | Finding Voronoi Regions; Closest Points; Polygon Triangulation. |
| Week 14 | Finding Star-Shaped Polygons; Finding Convex Hulls: Insertion Hull; Point Enclosure: The Ray-Shooting Method., Quiz VII |
| Week 15 | |
| Week 16 | Final Exam |
Assesment methods
| Course activities | Number | Percentage |
|---|---|---|
| Attendance | 14 | 5 |
| Laboratory | 0 | 0 |
| Application | 0 | 0 |
| Field activities | 0 | 0 |
| Specific practical training | 0 | 0 |
| Assignments | 0 | 0 |
| Presentation | 0 | 0 |
| Project | 0 | 0 |
| Seminar | 0 | 0 |
| Midterms | 7 | 60 |
| Final exam | 1 | 35 |
| Total | 100 | |
| Percentage of semester activities contributing grade succes | 0 | 65 |
| Percentage of final exam contributing grade succes | 0 | 35 |
| Total | 100 | |
WORKLOAD AND ECTS CALCULATION
| Activities | Number | Duration (hour) | Total Work Load |
|---|---|---|---|
| Course Duration (x14) | 14 | 3 | 42 |
| Laboratory | 0 | 0 | 0 |
| Application | 0 | 0 | 0 |
| Specific practical training | 0 | 0 | 0 |
| Field activities | 0 | 0 | 0 |
| Study Hours Out of Class (Preliminary work, reinforcement, ect) | 14 | 5 | 70 |
| Presentation / Seminar Preparation | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework assignment | 0 | 0 | 0 |
| Midterms (Study duration) | 7 | 8 | 56 |
| Final Exam (Study duration) | 1 | 20 | 20 |
| Total Workload | 36 | 36 | 188 |
Matrix Of The Course Learning Outcomes Versus Program Outcomes
| D.9. Key Learning Outcomes | Contrubition level* | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1. Applies contemporary methods, abilities, and tools essential for computer animation and game technologies. | X | ||||
| 2. Grasps the interdisciplinary interactions inherent to the field. | X | ||||
| 3. Examines the local or global influence of individuals, organizations, and communities on computer animation and game technologies. | X | ||||
| 4. Demonstrates comprehension and accountability in matters pertaining to professionalism, ethics, legality, security, and social issues. | X | ||||
| 5. Has the ability to effectively participate in a team created to achieve a common goal. | X | ||||
| 6. Possesses the ability to effectively participate in a team created to achieve a common goal. | X | ||||
| 7. Analyzes and defines a problem within their field and identifies appropriate solution processes required for suitable solutions. | X | ||||
| 8. Demonstrates the ability to apply the computer and mathematical knowledge required by the discipline. | X | ||||
| 9. Understands and is familiar with the principles and applications of algorithms and techniques in computer graphics and computer animation. | X | ||||
| 10. Utilizes technologies that capture and manipulate design elements to achieve the final production. | X | ||||
| 11. Apply principles of biomechanics and physics to animation | X | ||||
| 12. Uses procedural or interactive mechanisms to create animations. | X | ||||
| 13. Implements appropriate AI techniques in game development. | X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest