PoseNet is a powerful technology that allows computers to understand and track human poses in real-time. It uses deep learning algorithms to analyze images or videos and accurately estimate the positions of different body parts.
In simpler terms, think of PoseNet as a virtual "skeleton" that can be overlaid on a person's image or video. It can detect and track the positions of key body joints such as the head, shoulders, elbows, wrists, hips, knees, and ankles. This information is then used to create a digital representation of the person's pose.
PoseNet works by leveraging a deep neural network trained on a large dataset of labeled human poses. This training enables the model to learn the relationships between different body parts and how they move together. Once the model is trained, it can accurately predict the positions of body joints in new images or videos.
Here, PoseNet is being used as a motion capture tool.