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School of Engineering
- Undergraduate major in Mechanical Engineering
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- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
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School of Environment and Society
- Department of Architecture and Building Engineering
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- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Systems and Control Engineering
- Instructor(s)
- Okutomi Masatoshi
- Class Format
- Lecture
- Media-enhanced courses
- Day/Period(Room No.)
- Fri7-8(S223)
- Group
- -
- Course number
- SCE.I454
- Credits
- 1
- Academic year
- 2019
- Offered quarter
- 4Q
- Syllabus updated
- 2019/3/18
- Lecture notes updated
- -
- Language used
- English
- Access Index
-
Course description and aims
The main topic of this course is how to reconstruct 3-D information in space from 2-D images. This course will introduce several cues for reconstruction. Then geometric modeling between space and images, and methods for reconstruction based on the modeling will be explained. In addition, photometric modeling of images and scene reconstruction methods will be introduced.
Student learning outcomes
1. Understanding the outline of 3-D reconstruction from 2-D images.
2. Understanding the mathematical model which represents the geometric relation between space and images.
3. Understanding the methods for "stereo vision" and "structure from motion".
4. Understanding the photometric model of images and the methods for scene reconstruction, such as object shape, surface reflectance, and illumination.
Keywords
3-D reconstruction, geometric model, camera calibration, stereo vision, motion estimation, structure from motion, photometric model, reflectance characteristics
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | Practical and/or problem-solving skills |
Class flow
The outline of 3-D reconstruction from images, its fundamental theories and methods will be explained.
The contents might be changed according to students' knowledge and interests.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | Three Dimensional Reconstruction from Images | Understanding the essential problem of 3-D Reconstruction from images and the relation with human vision. |
| Class 2 | Geometric Relation between Space and Image | Understanding geometric modeling to represent space-image relation and subsequent equations. |
| Class 3 | Camera Calibration and Stereo Vision | Understanding camera calibration methods. Understanding the principle and equations of stereo vision. |
| Class 4 | Camera Motion Estimation and Structure from Motion | Understanding camera motion estimation. Understanding the problem to estimate both camera motion and 3-D positions. |
| Class 5 | Stereo Matching and Shape Recovery | Understanding stereo maching methods, how to use muti-view cameras, and shape recovery. |
| Class 6 | Photometric Analysis of Image | Understanding how the pixel values are determined and its mathematical models. |
| Class 7 | Reconstruction of Shape, Reflectance, and Illumination | Understanding the methods for reconstructing the object shape, surface reflectance characterristics, and/or illumination distribution from images. |
Textbook(s)
We will use the following reference book and handouts.
Reference books, course materials, etc.
Digital Image Processing: Computer Graphics Arts Society (CG-ARTS)
Assessment criteria and methods
The level of understanding about the contents presented in the course and the ability to apply them to problems will be asessed by submitted reports.
Related courses
- SCE.I501 ： Computaional Imaging
Prerequisites (i.e., required knowledge, skills, courses, etc.)
no prior conditions
