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.
Students are divided into groups. They are assigned to study some related topics, make presentation and present it in front of professors and other student groups.
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
Students are divided into groups. They are assigned to study some related topics, make presentation and present it in front of professors and other student groups.
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
The students are expected to be able to present their work confidently and effectively to audiences from various backgrounds and background levels.
The students are expected to be able to present their work confidently and effectively to audiences from various backgrounds and background levels.
| Goals and objectives | Course Outcomes | |
|---|---|---|
| 1. | The students can understand the fundamentals of image processing & computer vision |
A-1
|
| 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 ,
E
|
| 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 ,
E ,
D
|
| Mid-term | Final | Assignment | Attendance | Total. | |
|---|---|---|---|---|---|
| 1. | 10% | 10% | 20% | ||
| 2. | 10% | 20% | 30% | ||
| 3. | 0% | 0% | 30% | 20% | 50% |
| 4. | 0% | ||||
| Total. | 20% | 30% | 30% | 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) - Fundamental of image formation - Geometric formation |
Review what you learnt and do the assignments | 380分 |
| 2. | Image Formation (II) - Photometric Formation - Color |
Given papers are assigned to each student group | 380分 |
| 3. | • Early Vision (I) - Linear Filters & features • Group presentations |
In second half of class, each group will present their paper summarization Given papers are assigned to each student group |
380分 |
| 4. | • Early Vision (II) - Linear Filters & features (continued) • Group presentations |
In second half of class, each group will present their paper summarization Given papers are assigned to each student group |
380分 |
| 5. | • Early Vision (III) - Processing in frequency domain • Group presentations |
In second half of class, each group will present their paper summarization Given papers are assigned to each student group |
380分 |
| 6. | • Early Vision (IV) - Processing in frequency domain (continued) • Group presentations |
In second half of class, each group will present their paper summarization | 380分 |
| 7. | Mid-term examination and discussions on the solutions | Review all previous lessons Writing test with 10 questions for 180 minutes |
380分 |
| 8. | • Mid-level Vision (I) - Stereo Imaging (depth estimation, stereo matching, depth from stereo) - Structure from Motion |
Given papers are assigned to each student group | 380分 |
| 9. | • Mid-level Vision (II) - Segmentation - Tracking (optical flow, object tracking) • Group presentations |
In second half of class, each group will present their paper summarization Given papers are assigned to each student group |
380分 |
| 10. | • Mid-level Vision (III) - Image stitching and mosaicking • Group presentations |
In second half of class, each group will present their paper summarization Given papers are assigned to each student group |
380分 |
| 11. | • High-level Vision (I) - Object Detection - Object Recognition • Group presentations |
In second half of class, each group will present their paper summarization Given papers are assigned to each student group |
380分 |
| 12. | • High-level Vision (II) - 3D reconstruction • Group presentations |
In second half of class, each group will present their paper summarization | 380分 |
| 13. | • Machine learning basic | Review what you learnt | 380分 |
| 14. | Final exam and discussions on the solutions | Review all learnt lessons and practice for the final exam Writing test with 10 questions for 180 minutes |
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 (20%), Final Exam (30%), assignment (30%) and attendance (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 : Wed Sep 18 04:03:44 JST 2024