Deep Learning using OpenPose - Learn Pose Estimation Models and Build 5 AI Apps: The complete guide to creating your own Pose Estimation apps: Learn the full workflow and get up to speed with developing 5 AI apps

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: https://github.com/PacktPublishing/Deep-Learning-using-OpenPose---Learn-Pose-Estimation-Models-and-Build-5-AI-Apps

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.