Learn advanced hand pose estimation techniques using MediaPipe, OpenCV, and Python in this comprehensive tutorial video. Master the skills to detect left and right hands, calculate joint angles for kinematic analysis, and render estimated detections. Explore how to access baseline code, test real-time detections, extract landmarks for specific joints, and implement left and right hand detection. Dive into rendering hands using OpenCV, calculating hand kinematics, estimating angles for both static images and real-time scenarios, and computing various angle measurements. Gain practical knowledge to enhance your computer vision projects and expand your capabilities in hand pose estimation.
AI Hand Pose Estimation with MediaPipe - Detect Left and Right Hand and Calculate Angles
Overview
Syllabus
- Start
: - Introduction
- How it Works
- Tutorial Start
- Accessing Baseline Code
- Testing Real Time Detections
- Left and Right Hand Detection
- Extract Landmarks for a Specific Join
- Rendering Left and Right Hands using OpenCV
- Calculating Hand Kinematics
- Estimates Angles for an Image
- Estimating Angles in Real Time
- Calculating Different Angles
- Wrap Up
Taught by
Nicholas Renotte
Related Courses
-
AI Hand Pose Estimation with MediaPipe and Python
-
AI Pose Estimation with Python and MediaPipe - AI Gym Tracker Project
-
AI Face, Body and Hand Pose Detection with Python and Mediapipe
-
AI for Everyone - Real Time Pose Estimation with Mediapipe and Python
-
AI Body Language Decoder with MediaPipe and Python
-
Real Time AI Hand Pose Estimation with Javascript, Tensorflow.js and React.js
