Satya Mallick, PhD. – OpenCV For Beginners

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.

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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 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

Get your instant download Satya Mallick, PhD. – OpenCV For Beginners

• University of South Florida, Ph.D. in Computer Science
• Pioneered the creation of automated systems for the Deaf, which allow them to sign and communicate with other people by translating American Sign Language into English text
• Multiple research papers have been published in top conferences, including the IEEE Conference on Computer Vision & Pattern Recognition.-IEEE Transactions on Pattern Analysis, Machine Intelligence and other impact journals like IEEE Transactions on Pattern Analysis are just a few examples of scientific journals that have an impact.

• AI & Computer Vision Researcher and an Alumnus of Indian Institute of Science (IISc), Bangalore
• As part of a partnership, I lead the planning and development for our Computer Vision and AI courses. OpenCV
• More than a decade of rich experience in the field of AI Engineer, Data Scientist and Professor
• Snapdeal and Samsung have provided me with various Deep Learning, Computer Vision and Computer Vision projects.
• You are interested in research in the areas of Machine Perception, Scene Understanding and Deep Learning.

• Master’s degree in Aeronautics and Astronautics at Massachusetts Institute of Technology (MIT), with graduate courses in Machine Learning and Image Processing at Stanford University
• We have over 20 years of experience in space science and defense, and we are proud to have supported several major research programs and development efforts for more than two decades.
• Background in simulations and modelling, satellite systems, orbital analyses, and machine learning

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