Audio/Video Technology: Storage-Processing-Transmission
| Title | Τεχνολογία του Ήχου και της Εικόνας: Αποθήκευση, Επεξεργασία, Μετάδοση / Audio/Video Technology: Storage-Processing-Transmission |
| Code | 122 |
| Faculty | Engineering |
| School | Electrical and Computer Engineering |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Winter |
| Coordinator | Charalampos Dimoulas |
| Common | No |
| Status | Active |
| Course ID | 600001087 |
Programme of Study: Electrical and Computer Engineering
Registered students: 16
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| ELECTRICAL ENERGY | Elective Courses | 9 | 5 | 4 |
| ELECTRONICS AND COMPUTER ENGINEERING | Elective Courses | 9 | 5 | 4 |
| TELECOMMUNICATIONS | Elective Courses | 9 | 5 | 4 |
| Academic Year | 2022 – 2023 |
| Class Period | Winter |
| Faculty Instructors |
|
| Weekly Hours | 3 |
| Class ID | 600218196
|
Course Type 2016-2020
- Scientific Area
- Skills Development
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/1/600218196
- At the Website of the School:
- eLearning:
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Required knowledge of electives courses of the telecommunications sector: Electroacoustics Ι, Television Systems
Learning Outcomes
Upon successfully completing the course, the students will have mastered theoretical and applied knowledge for audiovisual signal capturing and digitization, recording media, processing methods, content analysis, and management tools. They will have comprehended data compression and information encodings (MPEG, JPEG, etc.), being familiarized with audio-video streaming systems and applications. They will have acquired know-how in audiovisual feature extraction and deployment, in machine learning and deep learning algorithms, in sophisticated services of multimedia semantics, management, and retrieval. Overall, the students will be able to comprehend and employ the contemporary audiovisual recording, processing, and broadcasting technologies, as they are progressed in the era of the Big Data and the Semantic Web.
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 teams
- Work in an international context
- Work in an interdisciplinary team
- Generate new research ideas
- Design and manage projects
Course Content (Syllabus)
Audiovisual signal capturing and digitization, Recording and reproduction of audio and video content (analog and digital media, linear/non-linear, tape/tape-less), Compression algorithms and standards of audio, image and video signals, Audio and television signal processing systems, Audio and video broadcasting, Web Radio /TV, High Definition (HD) Systems, Digital Cinema, Stereo (surround) multichannel audio systems, Stereoscopic vision, Audiovisual Content Management and Semantic processing Techniques.
Keywords
Audiovisual content - broadcasting, Compression algorithms, Digital media, Multimedia Semantics, Machine Learning
Educational Material Types
- Notes
- Slide presentations
- Video lectures
- Multimedia
- Interactive excersises
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Description
Use of slides (PowerPoint) during teaching the course. Providing additional material through the elearning platform (elearning.auth.gr). Contact students via email as well as the communication tools provided by the elearning platform. Evaluation through the tools provided by the elearning platform. Audiovisual processing, semantic analysis, content management and broadcasting tools.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 26 | 0.9 | ✓ | ||
| Project | 31 | 1.0 | ✓ | ||
| Written assigments | 18 | 0.6 | ✓ | ||
| Exams | 15 | 0.5 | ✓ | ||
| Total | 90 | 3 |
Student Assessment
Description
10% Participation in the lectures, presentation of the deliverables (personal evaluation - examination)
15% Topic presentation: Problem definition - Analysis (1st deliverable)
35% Final project presentation (2nd deliverable)
40% Final written essay – scientific paper (3rd deliverable)
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Assignment (Summative)
- Oral Exams (Summative)
- Performance / Staging (Formative, Summative)
- Report (Formative)
- Labortatory Assignment (Formative, Summative)
Bibliography
Additional bibliography for study
Σημειώσεις, διαδικτυακοί σύνδεσμοι, επιστημονικά άρθρα & διατριβές
Last Update
17-11-2020
