This course focuses on the recovery of the 3D structure of a scene from its 2D images. In particular, we are interested in the 3D reconstruction of a rigid scene from images taken by a stationary camera (same viewpoint). This problem is interesting as we want the multiple images of the scene to capture complementary information despite the fact that the scene is rigid and the camera is fixed. To this end, we explore several ways of capturing images where each image provides additional information about the scene.
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课程信息
Students should know the fundamentals of linear algebra and calculus. The knowledge of any programming language is beneficial, though not required.
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体验 Coursera 企业版您将学到的内容有
Learn radiometric concepts related to light and how it interacts with scenes.
Understand reflectance models and the different physical mechanisms that determine the appearance of a surface.
Develop a method for recovering the shape of a surface from its shading.
Understand the principle of photometric stereo where a dense surface normal map of the scene is obtained by varying the illumination direction.
您将获得的技能
- Photometric Stereo
- Depth from Focus and Defocus
- Structed Light Methods
- Reflectance Models
- Radiometry
Students should know the fundamentals of linear algebra and calculus. The knowledge of any programming language is beneficial, though not required.
对员工进行热门技能培训能否为您的公司带来益处?
体验 Coursera 企业版提供方
授课大纲 - 您将从这门课程中学到什么
Getting Started: 3D Reconstruction - Single Viewpoint
Radiometry and Reflectance
Photometric Stereo
Shape from Shading
审阅
- 5 stars85.71%
- 4 stars14.28%
来自3D RECONSTRUCTION - SINGLE VIEWPOINT 的热门评论
Professor Nayar is an amazing teacher and the lectures are pure gold. FPCV is a great introduction to computer vision.
Amazing course , Well explained and interesting assignments!!!
Excellent theoretical course, great content and the teacher explains very well. This course would be great with a complement of labs or small code practices.
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