Human pose estimation aims to locate the human body parts and build human body
representation (eg, body skeleton) from input data such as images and videos. It has drawn …

Advancements in modern medicine have bolstered the usage of home-based rehabilitation
services for patients, particularly those recovering from diseases or conditions that …

Most existing monocular 3D pose estimation approaches only focus on a single body part,
neglecting the fact that the essential nuance of human motion is conveyed through a concert …

From human physiology to environmental evolution, important processes in nature often
exhibit meaningful and strong periodic or quasi-periodic changes. Due to their inherent label …

The lung tumor is among the most detrimental kinds of malignancy. It has a high occurrence
rate and a high death rate, as it is frequently diagnosed at the later stages. Computed …

Single-photon–sensitive depth sensors are being increasingly used in next-generation
electronics for human pose and gesture recognition. However, cost-effective sensors …

In the era of deep learning, human pose estimation from multiple cameras with unknown
calibration has received little attention to date. We show how to train a neural model to …

We present a benchmark for 3D human whole-body pose estimation, which involves
identifying accurate 3D keypoints on the entire human body, including face, hands, body …

Human pose estimation is an important field of Computer Vision that aims to predict poses of
individuals from videos and images. It has been used in many different areas including …

The advent of computer vision technology and increased usage of video cameras in clinical
settings have facilitated advancements in movement disorder analysis. This review …