Landmark annotation is a specialized data labeling technique used to mark gestures and track the trajectory of human movements by identifying specific points in motion. This process enables machines to accurately recognize human faces, poses, and other intricate movements, making it essential for applications such as facial recognition, pose estimation, and gesture analysis.
In addition to gesture tracking, landmark annotations are widely used for detecting human figures and estimating poses in 2D images and videos. By pinpointing key landmarks on the body, such as joints or facial features, this technique allows AI models to interpret complex human motions with precision. These annotations are critical for various industries, including healthcare, sports analytics, virtual reality, and advanced machine learning systems for human-computer interaction
