Satya Mallick, PhD. – OpenCV For Beginners

Satya Mallick, PhD. - OpenCV For Beginners

Check it out: Satya Mallick, PhD. – OpenCV For Beginners

Have you ever wondered how Instagram filters work?

Or, how computers perform face detection in crowds?

Are you curious how virtual meeting applications blur the background or replace the background with other images?

How do self-driving cars navigate safely in a busy city environment?

Also, isn’t it amazing how the ball is tracked with such accuracy in televised sporting events such as Tennis, Soccer, and Basketball?

If we’ve piqued your curiosity then this course is what you need. Show your support by backing us right away and learn about topics in Computer Vision such as Object Tracking, Augmented Reality, Face Detection, Optical Flow, Human Pose Estimation and many more.

Unlike many Computer Vision courses available online, this hands-on course approaches Computer Vision more practically, experientially and intuitively. All you need is a working knowledge of the Python programming language. And, if you are not confident about your Python skills, we will direct you to some of the best-curated resources on Python, so that you come up to speed with Python in the shortest possible time.

In short, beginners, coding enthusiasts, start-up owners, Tony Stark fans – everyone is welcome to this introductory course.

OpenCV is the largest and the most popular Computer Vision library in the world. It is utilized by thousands of companies, products and devices, and is tested for scalability and performance every single day.

We, at OpenCV.org, are on a mission to educate a global workforce. We have been offering very comprehensive online courses in Computer Vision to professionals, job-seekers and enthusiasts from over 100 countries.

After the success of our first Kickstarter campaign in 2019, AI Courses By OpenCV.org, we want to make the practical knowledge of Computer Vision available to anyone who is interested in entering the world of Computer Vision.

Designed By Industry Experts: OpenCV For Beginners has been designed by our team of engineers and researchers, currently working in the field of Computer Vision and Deep Learning.
Powered By Python: The programming language of choice for this course is Python, one of the most comprehensive and widely used languages in AI.
Foundational & Experiential Learning: This course will help you develop essential understanding and practice of the subject matter before committing to more intermediate and advanced learning paths. This has been done using real-life examples which can be executed using your own data as well. As you proceed through the course, regular quizzes will also keep testing your level of understanding while providing important feedback to you.
Practical & Intuitive: The field of Computer Vision contains many theoretical underpinnings which can become a stumbling block for beginners, especially, when courses contain heavy mathematics. With this in mind, we have created this course with an emphasis on understanding through concrete, practical examples and explanations based on intuition rather than detailed mathematics which are covered in our advanced courses.

Once the course begins, we will provide you with extensive forum support in order to get you and your system ready for the course. We will always be there with you to troubleshoot any technical issues associated with software installation or executing any of the code provided in the course. Your questions will be answered by a team of instructors. In addition, we encourage you to brainstorm with your peers in the discussion forum and maybe even find a future collaborator to work with.

Each module in this well-structured course contains a tutorial introduction to a particular topic. This is followed by an application example to further reinforce the concepts. In these tutorials, we aim to provide the intuition necessary for true understanding as well as an explanation of the code. The applications developed in this course will be something you can actually use and build upon.

The unique curriculum offered in this course is aimed at providing you with a solid foundation in the field of Computer Vision. We will take great pride in each and everyone who completes it successfully. Upon completion of the course, we will award you with a digital certificate from OpenCV.org. You can showcase it across your social profiles and give a kickstart to your career and continued studies in the field of Computer Vision.

This course also gives you a fantastic chance to win lifetime access to another course of your choice. All you need to do is submit a project that you created during the course, end up in the top three of all submissions and get lifetime access to a course of your choice for FREE along with getting featured on the OpenCV.org website.

Have a look at some of the applications we plan to offer in this course.

Getting Started With Images

Image basics (reading, displaying and writing images)
Working with video files (reading, displaying and writing videos)
Color space conversion and different color spaces
Basic image manipulation (resizing, cropping, annotating, creating a Region of Interest)

Basic Image Operations

Mathematical operations on images (brightness and contrast)
Image thresholding, bitwise operations and masking
Image blending and the alpha channel

Image Enhancement Techniques

Image filtering using convolution
Image blurring, noise reduction and sharpness
Artistic rendering

Image Analysis

Edge detection
Hough transforms
Contour and shape detection
Working with different types of image data such as satellite imagery

Augmented Reality

ArUco markers and augmented reality
Human-Computer Interaction (HCI) using gestures

Computational Photography

Image restoration

Image Retrieval and Object Detection

Finding good features in images like SIFT, ORB
Image hashing
Geometric transformations like affine transformation and homography

Video Processing

Object tracking
Optical flow and motion estimation

OpenCV DNN Module

OpenCV DNN inference module
Face detection using Deep Learning
Object detection using Deep Learning
Human pose estimation using Deep Learning

Text In Images (OCR)

Text spotting and detection using Deep Learning
Text recognition and Optical Character Recognition (OCR) using Deep Learning

Using OpenCV High-Level GUI For Creating Applications

Using mouse and keyboard with OpenCV

Creating Web Applications Using Streamlit

Streamlit framework for building web-based applications

Ethical And Socially Responsible Ways Of Using OpenCV

All courses offered in our Kickstarter bundles, including OpenCV For Beginners, are the only official and certified courses by OpenCV.org available online.

The courses are created in collaboration with Big Vision LLC, a California-based Computer Vision and Machine Learning consulting company. Big Vision LLC owns the popular Computer Vision blog LearnOpenCV.com, and is the exclusive and official course provider of OpenCV.org. Have a look at the industry experts that form our core course team.

One of the top 30 AI influencers to follow on Twitter as per IBM Watson blog (2017)
Alumnus of Indian Institute of Technology (IIT), Kharagpur and Ph.D. from the University of California (San Diego)
Author of Computer Vision blog LearnOpenCV.com
Work featured in publications such as BBC, Time, Huffington Post, Wall Street Journal, Oprah Magazine, TechCrunch and TheRegister.co.uk

BS from University of California, Berkeley and Ph.D. from Boston University in AI, Machine Learning and Neuro-Modelling
Served as a Visiting Professor at Computer Science Department, Stanford University for 7 years
Founder of the most powerful and popular Computer Vision library in the world, OpenCV.org
Organized the Computer Vision team for Stanley, the autonomous car that won the $2M DARPA Grand Challenge and currently displayed at the Smithsonian Air and Space Museum

Ph.D. in Computer Science from the University of South Florida
Pioneered the development of automated systems for the Deaf community, helping them sign and communicate with others by translating American Sign Language to English text
Published multiple research papers in top scientific conferences including IEEE Conference on Computer Vision and Pattern Recognition, and high-impact scientific journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence

AI & Computer Vision Researcher and an Alumnus of Indian Institute of Science (IISc), Bangalore
Leading planning and development of our Computer Vision and AI courses, in partnership with OpenCV
Over a decade of rich experience as Professor, AI Engineer and Data Scientist
Worked on various Deep Learning and Computer Vision projects with Samsung and Snapdeal
Interested in doing research in the field of Machine Perception, Scene Understanding, Deep Learning and Robotics

Masters degree in Aeronautics and Astronautics from Massachusetts Institute of Technology (MIT), including graduate course work in Machine Learning and Image Processing at Stanford University
Extensive experience in the space science and defense industries, supporting several major development programs and research efforts for over two decades
Background in modelling and simulations, satellite systems, orbital analysis and machine learning