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3D Reconstruction - Multiple Viewpoints

Master 3D scene reconstruction techniques using multi-view geometry and camera calibration for accurate digital model creation.

Master 3D scene reconstruction techniques using multi-view geometry and camera calibration for accurate digital model creation.

This comprehensive course explores methods for recovering 3D structure from multiple viewpoints in computer vision. Students learn camera calibration, stereo vision systems, structure from motion, and optical flow estimation. The course covers both theoretical foundations and practical applications in robotics, virtual reality, and autonomous navigation.

4.7

(39 ratings)

3,938 already enrolled

Instructors:

English

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3D Reconstruction - Multiple Viewpoints

This course includes

72 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Master camera calibration techniques

  • Develop stereo vision systems

  • Implement structure from motion algorithms

  • Create optical flow estimations

  • Understand epipolar geometry

  • Build 3D scene reconstruction systems

Skills you'll gain

3D Reconstruction
Camera Calibration
Stereo Vision
Structure from Motion
Optical Flow
Computer Vision
Epipolar Geometry
Scene Modeling

This course includes:

4.2 Hours PreRecorded video

25 assignments

Access on Desktop

FullTime access

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There are 5 modules in this course

This advanced course provides comprehensive coverage of 3D reconstruction techniques using multiple viewpoints. Students learn the complete pipeline from camera modeling and calibration to complex scene reconstruction. The curriculum covers stereo vision, uncalibrated reconstruction, optical flow estimation, and structure from motion algorithms.

Getting Started: 3D Reconstruction - Multiple Viewpoints

Module 1 · 2 Hours to complete

Camera Calibration

Module 2 · 16 Hours to complete

Uncalibrated Stereo

Module 3 · 20 Hours to complete

Optical Flow

Module 4 · 16 Hours to complete

Structure from Motion

Module 5 · 17 Hours to complete

Fee Structure

Instructor

Shree Nayar
Shree Nayar

4.8 rating

44 Reviews

18,258 Students

5 Courses

T. C. Chang Professor of Computer Science

Shree K. Nayar is the T. C. Chang Professor of Computer Science at Columbia University, where he leads the Columbia Vision Laboratory (CAVE). His laboratory specializes in developing cutting-edge computational imaging and computer vision systems. Nayar’s research focuses on three primary areas: the creation of innovative cameras that offer new types of visual information, the design of physics-based models for vision and graphics, and the development of algorithms aimed at understanding and interpreting scenes from images.Professor Nayar’s work is highly interdisciplinary, bridging the domains of imaging, computer vision, robotics, virtual and augmented reality, visual communication, computer graphics, and human-computer interaction. His pioneering research has significant real-world applications in these fields, advancing both the technology and our understanding of visual systems.In addition to his research, Nayar is an educator, teaching several advanced courses at Columbia University, including 3D Reconstruction - Multiple Viewpoints, 3D Reconstruction - Single Viewpoint, Camera and Imaging, Features and Boundaries, and Visual Perception. These courses reflect his expertise in computer vision and imaging technologies and contribute to shaping the next generation of researchers and engineers in these fields.

3D Reconstruction - Multiple Viewpoints

This course includes

72 Hours

Of Self-paced video lessons

Beginner Level

Completion Certificate

awarded on course completion

Free course

Testimonials

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Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.