For years, multimedia has played a pivotal role in various aspects of Computer Science and Engineering, becoming a crucial
component in fields such as image processing, computer vision, computer networks, real-time systems, and information retrieval.
As such, acquiring a comprehensive understanding of multimedia is increasingly becoming essential, underscoring the significance
of this course. The curriculum covers key areas, including image processing (both in spatial and frequency domains), and computer
vision (encompassing feature extraction, detection, recognition, and 3D reconstruction, etc). Through this course, students
will gain a robust foundation of knowledge, equipping them to conduct research in various cutting-edge topics within multimedia
technologies, such as image and video processing, and image rendering.
The course will be conducted in-person (face-to-face) in Fall 2024. Students who are overseas and wish to enroll in this class should contact the lecturer via email
The course will be conducted in-person (face-to-face) in Fall 2024. Students who are overseas and wish to enroll in this class should contact the lecturer via email
The students are expected to learn fundamental knowledge of multimedia in conjunction with real applications
| Goals and objectives | Course Outcomes | |
|---|---|---|
| 1. | The students can understand the fundamentals of image processing & computer vision |
A-1
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| 2. | The students can understand the concepts in image processing & computer vision through various applications. They are also expected to develop applications as the assignments. |
A-1
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| 3. | The students themselves can develop good skills in programming, teamworks, critical thinking, etc. They can also develop good attitude during studying, e.g., proactively discuss with classmates and lecturer, attend the class in time, submit the assignment in time, no cheating during the exam. |
A-1
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| Mid-term | Final | Attitude during class | Total. | |
|---|---|---|---|---|
| 1. | 15% | 20% | 0% | 35% |
| 2. | 15% | 30% | 0% | 45% |
| 3. | 0% | 0% | 20% | 20% |
| Total. | 30% | 50% | 20% | - |
| Class schedule | HW assignments (Including preparation and review of the class.) | Amount of Time Required | |
|---|---|---|---|
| 1. | Introduction to image processing & computer vision Image Formation (I) |
Review what you learnt and do the assignments | 380分 |
| 2. | Image Formation (II) Spatial image processing (I) |
Review what you learnt and do the assignments | 380分 |
| 3. | Spatial image processing (II) | Review what you learnt and do the assignments | 380分 |
| 4. | Frequency domain processing (II) | Review what you learnt and do the assignments | 380分 |
| 5. | Photometry & color processing | Review what you learnt and do the assignments | 380分 |
| 6. | Deep learning for computer vision | Review what you learnt and do the assignments | 380分 |
| 7. | Mid-term examination and discussions on the solutions | Review all previous lessons | 380分 |
| 8. | Introduction to features: features detection & matching | Review what you learnt and do the assignments | 380分 |
| 9. | Matching and stitching | Review what you learnt and do the assignments | 380分 |
| 10. | Detection & Recognition | Review what you learnt and do the assignments | 380分 |
| 11. | Motion estimation and its problems | Review what you learnt and do the assignments | 380分 |
| 12. | Stereo & camera models | Review what you learnt and do the assignments | 380分 |
| 13. | Depth estimation & 3D reconstruction | Review what you learnt and do the assignments | 380分 |
| 14. | Final exam and discussions on the solutions | Review all learnt lessons and practice for the final exam | 380分 |
| Total. | - | - | 5320分 |
| A:Fundamental Mechanical Engineering | B:Advanced Mechanical Engineering | C:Environment and Materials Engineering | D:Chemistry and Biotechnology | E:Electrical Engineering and Robotics | G:Advanced Electronic Engineering | F:Information and Communications Engineering | L:Computer Science and Engineering | H:Urban Infrastructure and Environment |
|---|
Midterm exam (30%), Final Exam (50%) and Attitude During Class (20%) are the criteria of the grade. More than 60% of the total
score is needed for getting the course credit.
<Note>
Students are marked absent from the class if they are late regardless of the delay time.
If students are absent from more than one third of the total number of classes, the credit of this course cannot be given to them.
Even though students are absent from the class whatever the reason, e.g. sickness, delay of public transportation systems, forgetting to bring the student ID card, it is counted as absence.
<Note>
Students are marked absent from the class if they are late regardless of the delay time.
If students are absent from more than one third of the total number of classes, the credit of this course cannot be given to them.
Even though students are absent from the class whatever the reason, e.g. sickness, delay of public transportation systems, forgetting to bring the student ID card, it is counted as absence.
| ways of feedback | specific contents about "Other" |
|---|---|
| Feedback in the class | Feedbacks on exams, assignments, etc can be done either in class, via scomb or email. |
1. Digital Image processing 4e, Gonzalez Rafael 2017
2. Computer Vision: Algorithms and Applications 2nd Edition, Richard Szeliski, 2021
3. Multiple view geometry in Computer vision, 2nd edition, Richard Hartley, 2004
2. Computer Vision: Algorithms and Applications 2nd Edition, Richard Szeliski, 2021
3. Multiple view geometry in Computer vision, 2nd edition, Richard Hartley, 2004
- Course that cultivates an ability for utilizing knowledge
| Work experience | Work experience and relevance to the course content if applicable |
|---|---|
| N/A | N/A |
Last modified : Thu Mar 14 04:08:40 JST 2024