Recognizing human activities from video sequences or still images is a challenging task due
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …

Video based action recognition is one of the important and challenging problems in
computer vision research. Bag of visual words model (BoVW) with local features has been …

In this paper, we propose a structured feature learning framework to reason the correlation
among body joints at the feature level in human pose estimation. Different from existing …

We address action recognition in videos by modeling the spatial-temporal structures of
human poses. We start by improving a state of the art method for estimating human joint …

Traditionally, inertial measurement unit (IMU)-based human joint angle estimation
techniques are evaluated for general human motion where human joints explore all of their …

Traditionally, inertial measurement units-(IMU) based human joint angle estimation requires
a priori knowledge about sensor alignment or specific calibration motions. Furthermore …

The visual recognition of complex, articulated human movements is fundamental for a wide
range of artificial systems oriented toward human-robot communication, action classification …

This paper proposes a novel approach to tackle the challenging problem of'online action
localization'which entails predicting actions and their locations as they happen in a video …

Action analysis in image and video has been attracting more and more attention in computer
vision. Recognizing specific actions in video clips has been the main focus. We move in a …

This paper proposes a person-centric and online approach to the challenging problem of
localization and prediction of actions and interactions in videos. Typically, localization or …