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 …

Highlights•Deep neural networks are shattering performance benchmarks in computer
vision for various tasks.•Using modern deep learning approaches (DNNs) in the lab is a …

Vision-based monocular human pose estimation, as one of the most fundamental and
challenging problems in computer vision, aims to obtain posture of the human body from …

Background The study of human movement within sports biomechanics and rehabilitation
settings has made considerable progress over recent decades. However, develo** a …

Extracting behavioral measurements non-invasively from video is stymied by the fact that it is
a hard computational problem. Recent advances in deep learning have tremendously …

To understand and analyze human behavior, we need to capture humans moving in, and
interacting with, the world. Most existing methods perform 3D human pose estimation …

Human pose estimation has received significant attention recently due to its various
applications in the real world. As the performance of the state-of-the-art human pose …

This paper proposes a new hybrid architecture that consists of a deep Convolutional
Network and a Markov Random Field. We show how this architecture is successfully applied …

Human-centered computing is an emerging research field that aims to understand human
behavior and integrate users and their social context with computer systems. One of the …

There is a large variety of trackers, which have been proposed in the literature during the
last two decades with some mixed success. Object tracking in realistic scenarios is a difficult …