A Review on Human Pose Estimation
It provides a comprehensive overview for researchers in computer vision, but is incremental as it synthesizes existing knowledge without new results.
This paper reviews the problem of Human Pose Estimation (HPE), which involves localizing human joints in images and videos, covering classical approaches and deep learning models.
The phenomenon of Human Pose Estimation (HPE) is a problem that has been explored over the years, particularly in computer vision. But what exactly is it? To answer this, the concept of a pose must first be understood. Pose can be defined as the arrangement of human joints in a specific manner. Therefore, we can define the problem of Human Pose Estimation as the localization of human joints or predefined landmarks in images and videos. There are several types of pose estimation, including body, face, and hand, as well as many aspects to it. This paper will cover them, starting with the classical approaches to HPE to the Deep Learning based models.