Deep Learning using OpenPose - Learn Pose Estimation Models and Build 5 AI Apps

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The complete guide to creating your own Pose Estimation apps: Learn the full workflow and get up to speed with developing 5 AI apps.

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16 on-demand videos & exercises
Level: Beginner
41 mins
Access on mobile, web and TV

What to know about this course

Pose Estimation is a computer vision technique that can detect human figures in both images and videos. You may have first experienced Pose Estimation if you've played with an Xbox Kinect or a PlayStation Eye. But, imagine developing your own Pose Estimation applications without the specialized hardware, using just using an ordinary webcam and the power of artificial intelligence (AI). Whether you want to apply this technology for character animation, video games, assisted driving systems or even medical applications, this course can help you achieve your goal quickly and effectively. You’ll get started with Pose Estimation, from learning the fundamentals of the technology through to implementing the OpenPose framework in real-time.

You will also understand how to adapt this framework for 5 practical applications on:
•Fall detection
•Counting people
•Yoga pose identification
•Plank pose correction
•Automatic body ratio calculation

All along, you will get to grips with deep learning, using AI to understand human actions and behaviors. By the end of this course, you will be well-versed with the OpenPose framework and have developed the skills you need to develop immersive AI applications. All code and supporting files for this course are available at:

Who's this course for?

This course is for anyone who wants to learn how to perform Pose Estimation, and explore practical approaches to Pose Estimation. Having Python, OpenCV, or AI experience will be useful.

What you'll learn

  • Understand Pose Estimation.
  • Learn how to implement your own fall detection app.
  • Use OpenPose to count people.
  • Apply Pose Estimation for yoga pose identification.
  • Ensure perfect planking and push-up posture with OpenPose.
  • Calculate real-time body ratios.

Key Features

  • Learn and implement OpenPose Deep Learning Pose Estimation models.
  • Learn how to execute OpenPose.

Course Curriculum

About the Author

Ritesh Kanjee, Geeky Bee AI Pvt. Ltd.

Augmented Startups have over 8 years experience in Printed Circuit Board (PCB) design as well in image processing and embedded control. Author Ritesh Kanjee has completed his Masters Degree in Electronic engineering and published two papers on the IEEE Database with one called "Vision-based adaptive Cruise Control using Pattern Matching" and the other called "A Three-Step Vehicle Detection Framework for Range Estimation Using a Single Camera" (on Google Scholar). His work was implemented in LabVIEW. He works as an embedded electronic engineer in defence research and has experience in FPGA design with programming in both VHDL and Verilog. He also has expertise in augmented reality and machine learning in which he shall be introducing new technologies through the medium of video. Geeky Bee AI Pvt Ltd (The Artificial Intelligence Solution Provider) offers development in the field of computer vision, deep learning and automation to solve complex challenges for clients across the world.

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