This is an introductory course for computer vision, covering core fundamentals in detail. The programming language used in the course is Python/C++.
This course was developed in collaboration with Swaayatt Robots, and thus the introductory lectures cover autonomous driving and robotics to provide an introduction to computer vision and its application to those respective fields at large.
This course was initially offered as a first module of the Introduction to Robotics and Visual Navigation course (RO-1.0X). It covers more computer vision topics than the earlier RO-1.0X Module-1, and serves as a standalone foundational computer vision course.
Basic Python / C++ Programming
Basic Linear Algebra and Calculus
Library independent algorithm implementation
Covers core mathematics fundamentals
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.
1. Perception: Indoor and Outdoor
2. Mapping and Localization
1. Sensors: LiDARs and Cameras, RADAR (not so much)
2. Images and Image Channels
3. Color Spaces
1. Different Noise Models
1. Spatial vs Frequency Domain
2. Spatial Domain Processing
3. Histogram Equalization: Motivation and Algorithm
4. Adaptive Histogram Equalization
1. Image Smoothing
2. Morphological Operations: Erosion, Dilation, Opening, Closing
3. Morphological Image Smoothing
4. Image Smoothing with Edge Preservation
5. Edge Detection
1. Corner Detectors
2. Blob Detectors
3. Image Descriptors
1. Epipolar Geometry
2. Feature Matching
3. RANSAC for Robust Feature Matching
1. Super Pixel Methods
2. K-Means Clustering
3. Kernel Density Estimation
4. Mean-Shift Clustering
5. Graph Based Methods
1. Hough Transform (confirmed)
2. Hough Transform: Lane Detection (confirmed)
3. Optical Flow (not confirmed)
4. Reverse Optical Flow Application: Road Detection (not confirmed)
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).
- 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 20+ assignments.
Almost every topic will have at least one assignment in the course.
Instructor’s NameSanjeev Sharma
Free videosClick Here
Fee: India₹ 65000
Fee: Foreign₹ 70000
First Offered:RO1.0X (2020)
Current Status:Starts From 12th Dec
Expected Course Engagement10-15 Hrs/Week