Master 3D scene reconstruction techniques, from radiometry to active illumination. Perfect for computer vision beginners.
Master 3D scene reconstruction techniques, from radiometry to active illumination. Perfect for computer vision beginners.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full First Principles of Computer Vision Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.9
(35 ratings)
4,316 already enrolled
Instructors:
English
What you'll learn
Learn fundamental radiometric concepts and light interaction
Master reflectance models and surface appearance mechanisms
Develop methods for shape recovery from surface shading
Understand and implement photometric stereo techniques
Explore depth from focus and defocus principles
Master active illumination methods for 3D reconstruction
Skills you'll gain
This course includes:
6.7 Hours PreRecorded video
31 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 6 modules in this course
This comprehensive course focuses on recovering 3D structure from 2D images using a stationary camera. Students learn essential radiometric concepts, shape recovery techniques, and advanced methods like photometric stereo and depth from defocus. The curriculum covers both theoretical foundations and practical applications, from basic reflectance models to industrial automation solutions. The course emphasizes hands-on learning through multiple assignments and real-world examples, preparing students for both academic research and industry applications.
Getting Started: 3D Reconstruction - Single Viewpoint
Module 1 · 2 Hours to complete
Radiometry and Reflectance
Module 2 · 19 Hours to complete
Photometric Stereo
Module 3 · 19 Hours to complete
Shape from Shading
Module 4 · 16 Hours to complete
Depth from Defocus
Module 5 · 13 Hours to complete
Active Illumination Methods
Module 6 · 17 Hours to complete
Fee Structure
Instructor
Pioneer in Computational Imaging and Professor at Columbia University
Dr. Shree K. Nayar is the T. C. Chang Professor of Computer Science at Columbia University, where he leads the Columbia Vision Laboratory (CAVE). His research focuses on computational imaging and computer vision, with key interests in developing novel camera systems, physics-based models for vision and graphics, and algorithms for scene understanding from images. Dr. Nayar's work has significant applications across various fields, including robotics, virtual reality, augmented reality, and human-computer interfaces.He holds a B.E. in Electrical Engineering from the Birla Institute of Technology, an M.S. in Electrical and Computer Engineering from North Carolina State University, and a Ph.D. from Carnegie Mellon University. Throughout his career, Dr. Nayar has received numerous accolades for his contributions to the field, including the 2010 ACM Software Systems Award for his work on the GroupLens Recommender System. He has published over 300 scientific papers and holds more than 80 patents related to imaging technologies.Dr. Nayar teaches several courses on Coursera, including "3D Reconstruction - Multiple Viewpoints" and "Camera and Imaging," aimed at providing students with foundational knowledge in computer vision and imaging systems.
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4.9 course rating
35 ratings
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