CV-2.0X: Introduction to Visual Odometry and Mapping

Course Details

Course Details

This is an introductory course for visual odometry and mapping, covering core fundamentals in detail. The programming language used in the course is Python/C++. 


  • Basic Python / C++ Programming

  • Basic Linear Algebra and Calculus

  • CV-1.0X: Introduction to Computer Vision

Course Highlights

  •  Library independent algorithm implementation

  •  Covers core mathematics fundamentals

Payment Modes:

We have two options:

  • Pay online using payment gateway

  • Pay via Bank Transfer

  • In Bank transfer, during refund, there is no payment-gateway fee deduction.

This course begins with an introduction to the working principle of a camera. We provide an in-depth overview of the various coordinate systems involved in camera geometry (projection). Then, we discuss the various parameters involved in the camera calibration process and also explain the camera calibration process in detail.

1. Coordinate System Transformation

2. Intrinsic and Extrinsic Parameters

3. Pinhole Projection Model

Introduction to 2D Camera Calibration Process

Singular Value Decomposition for Computing Homography

1. Lens Distortion

2. Homography Matrix

3. Computing Intrinsic Parameters and Lens Distortion Parameters

In this module, we take a deeper look at the various feature-matching techniques to find corresponding feature matches between images. This plays a very crucial role in the Visual Odometry and Mapping pipeline. We also discuss an algorithm to perform outlier rejection and estimate the feature matches in a more robust manner.

1. Feature Matching

2. RANSAC Algorithm

3. RANSAC for Robust Feature Matching

Visual Odometry as the name suggests, is very much dependent on information from sensors, primarily the sensors for performing active perception, mainly, Cameras and LiDAR’s. This module begins by asking the fundamental question of how a point in 3D is transformed across multiple views and can there be a mathematical formulation for the same. In answering this question, we discuss fundamental concepts like multi-view geometry, elipolar geometry, and essential and fundamental matrices. We also discuss algorithms to compute these matrices.

1. Epipolar Geometry

2. Essential Matrix

3. Fundamental Matrix

4. 8-point Algorithm

This module discusses various methodologies to compute motion across frames (in time as the camera moves in the environment). This includes 2D-2D motion estimation, 3D-2D motion estimation, and 3D-3D motion estimation.

1. 2D-2D Motion Estimation

2. 3D-2D Motion Estimation

3. 3D-3D Motion Estimation

This module discusses triangulation, which answers the question of how the 3D points in the world can be estimated given that we are able to to track the motion of the camera.

1. Triangulation

In this module, we discuss core concepts involved in the mapping pipeline. This involves the backend part of the pipeline. The backend part includes loop closure detection and optimization. All these concepts will be discussed in great mathematical detail along with accompanying examples. We will also be introducing the G2O library which would be used for performing Bundle Adjustment and Pose Graph Optimization.

1. Introduction to Mapping

2. Bag of Visual Words

3. Global Descriptors

1. Introduction to G2O

1. Introduction to Bundle Adjustment

1. Global Bundle Adjustment

2. Pose Graph Optimization


6 Months from the date of registration or from course start date, whichever is later.

Beyond this period, registrant will have to pay 10% of the course fee for extension of 2 months for charges related to server, maintainence, and assignment evaluation.

Refunds can be done only within 7 days of registration. In case any part of the course becomes online, for that part refund cannot be issued. We recommend checking the free lectures to get an idea of the depth and type of lectures in the course before one registers for the course.

If a refund is requested by a registrant, we will subtract the payment-gateway fee from your payment. An additional 1% of the amount will be deducted for convenience, processing, and server charges. The GST amount will also be subtracted. Any part of the course that is online, fee corresponding to that part will also be deducted. The remaining amount will be refunded to you.

The below example shows the refund process in case of a full refund, i.e., when the course has not become online. 

Payment gateway fee when you make a payment (course fee + tax):

  • National 2.36%: 2% + 18% GST on 2%
  • International 3.54%: 3% + 18% GST on 3%

Amount received by us, denoted by M, after you make a payment of amount X, where y is the payment-gateway fee share (2.36% or 3.54%):

  • X = x + x*18/100
  • M = X - X*y/100
  • Where "x" is the course fee without the GST, and "X" is the course fee with GST (if we are collecting GST).

Refund Process

  • Amount received by us, denoted by M: M = X - X*y/100
  • Refund initiated by us, denoted by N: N = M - M*1.18/100
  • Refund amount uploaded on payment-gateway to be refuned to you after GST subtraction: N - x*0.18
  • Amount refunded to you by the payment-gateway: N - N*y/100

Refund Process, if payment was made via direct bank transfer:

  • Amount received by us: X = x + x*18/100 (if GST is collected)
  • Refund initiated by us: N = X - X*1.18/100 - x*18/100
  • Amount refunded to you: N


This course has 10+ assignments.

Almost every topic will have at least one assignment in the course.

  • Instructor’s Name

    Sanjeev Sharma
  • Course Type

  • Fee: India

          ₹ 60000
  • Fee: Foreign

    ₹ 80000
  • Current Status:

    Coming Soon
  • Expected Course Engagement

    10-15 Hrs/Week