Human Pose Estimation is a general problem in Computer Vision where we detect the position and orientation of an object. This usually means detecting keypoint locations that describe the object as per requirement for specific positions.
The basic idea of human pose estimation is understanding people’s movements in videos and images. By defining keypoints (joints) on a human body like wrists, elbows, knees, and ankles in images or videos, the deep learning-based system recognizes a specific posture in space. Basically, there are two types of pose estimation: 2D and 3D. 2D estimation involves the extraction of X, Y coordinates for each joint from an RGB image, and 3D – XYZ coordinates from an RGB image.
Pose Estimation Algorithm
The sequential prediction framework of the pose machine provides a natural approach to training our deep architecture that addresses specific requirement
**Follow the steps for live experience
- Keep any object infront of webcam
- Wait till object get stable
- Live feed detect object and show its name
- Try other object
(**To be launch soon)
Computer Vision Development Tools
Our team builds advanced computer vision solutions. When developing Human Pose Estimation and Analysis Software, we use cutting-edge technologies to deliver solutions that will address your business challenges.
Deep Learning
Keras
OpenCV
TensorFlow
Python
