COMPUTER VISION
| Title | ΥΠΟΛΟΓΙΣΤΙΚΗ ΟΡΑΣΗ / COMPUTER VISION |
| Code | NDM-08-01 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Coordinator | Ioannis Pitas |
| Common | No |
| Status | Active |
| Course ID | 600019808 |
Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)
Registered students: 16
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| GENIKĪ KATEUTHYNSĪ | YPOCΗREŌTIKO KATA EPILOGĪ | 8 | 4 | 5 |
| Academic Year | 2020 – 2021 |
| Class Period | Spring |
| Faculty Instructors |
|
| Weekly Hours | 3 |
| Class ID | 600180123
|
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600180123
- At the Website of the School:
- Other: www.aiia.csd.auth.gr
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Basic mathematical knowledge. Programming knowledge (C/C++, or Python, MATLAB. Capabilities to study scientific literature in English.
Learning Outcomes
Cognitive:Image segmentation. Image texture. Image features. Image registration. Image search and retrieval. Image topology. 2D shape description and recognition. Moving images. Motion estimation. Object tracking. Video description. Video search and retrieval.
Skills: Background knowledge for further study of problems and applications of artificial vision and image / video analysis. Analytical and programming skills. Ability to develop basic digital image and video analysis applications using C / C ++, MATLAB, Python.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Work in an international context
- Work in an interdisciplinary team
- Generate new research ideas
- Design and manage projects
- Be critical and self-critical
- Advance free, creative and causative thinking
Course Content (Syllabus)
Image segmentation. Image texture. Image features. Image registration. Image search and retrieval. Image topology. 2D shape description and recognition. Moving images. Motion estimation. Object tracking. Video description. Video search and retrieval.
Keywords
Computer vision, image/video analysis
Educational Material Types
- Notes
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Communication with Students
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 80 | ✓ | |||
| Reading Assigment | 15 | ✓ | |||
| Project | 20 | ✓ | |||
| Written assigments | 15 | ✓ | |||
| Exams | 20 | ✓ | |||
| Total | 150 |
Student Assessment
Description
Optional/obligatory projects and final exams.
Student Assessment methods
- Written Exam with Extended Answer Questions (Formative, Summative)
- Written Assignment (Formative, Summative)
- ΝΑΙ
Bibliography
Course Bibliography (Eudoxus)
1. Πήτας Ι. «Ψηφιακή Επεξεργασία Εικόνας», Θεσσαλονίκη, 2010. 2. Πήτας Ι. «Ψηφιακή Επεξεργασία Βίντεο-Ψηφιακή Τηλεόραση», Θεσσαλονίκη, 2010.
Additional bibliography for study
1. R. Szelinski, Computer Vision, Springer 2011, 2. M. Tekalp, "Digital Video Processing", Prentice Hall PTR, 1996. 3. Yao Wang, Jorn Ostermann, and Ya-Qin Zhang, "Video Processing and Communications", Prentice Hall, 2001.
Last Update
07-12-2020
