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Landmark Annotation for Face Recognition and Human Pose Detection

By April 10, 20202 Mins Read
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Landmark point annotation is use to detect the human faces and poses with high accuracy. Each point on faces are drawn to measure the faces of humans and their expressions. It helps to detect facial features, expressions, emotions and poses of humans or other types of objects of interest.    

Landmark Annotation for Pose Detection in Sports analysis

In sports and outdoor games, athletes perform different types of actions, and to detect such human actions by AI models or machines, landmark annotation techniques is used in machine learning. Such AI and ML models, can easily learn if they are annotated with landmarking annotation technique.

Landmark annotation

Landmark Point Annotation for Precise Facial Recognition        

AI based camera in security surveillance or smartphones can detect the humans through their faces to differentiate. And to train such computer vision model through deep learning, land marking annotated images are used by machine learning engineers. It can measure the line and length measure the facial attributes and identify the human faces to differentiate them and provide the useful information.

Key Point Annotation for Gesture Recognition in Humans

Landmark annotation is also used to annotate the human faces to identify the gestures and their expressions. The human face is annotated precisely, from each point to another to make the human face recognizable with their expression and their gestures. Its helps machines to understand the gestures and expressions through various devices like smartphones and AI cameras.

Cogito provides the landmark point annotation solution with best image annotation infrastructural facilities. It has world-class annotators to precisely annotate the images and provide the best quality training datasets with landmarking annotation at most affordable. It is also expert in image annotation service to provide world-class data annotation service for AI and machine learning.

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