Human action recognition and prediction: A survey
Derived from rapid advances in computer vision and machine learning, video analysis tasks
have been moving from inferring the present state to predicting the future state. Vision-based …
have been moving from inferring the present state to predicting the future state. Vision-based …
Memory attention networks for skeleton-based action recognition
Skeleton-based action recognition has been extensively studied, but it remains an unsolved
problem because of the complex variations of skeleton joints in 3-D spatiotemporal space …
problem because of the complex variations of skeleton joints in 3-D spatiotemporal space …
A framework of human detection and action recognition based on uniform segmentation and combination of Euclidean distance and joint entropy-based features …
Human activity monitoring in the video sequences is an intriguing computer vision domain
which incorporates colossal applications, eg, surveillance systems, human-computer …
which incorporates colossal applications, eg, surveillance systems, human-computer …
Watch-n-patch: Unsupervised understanding of actions and relations
We focus on modeling human activities comprising multiple actions in a completely
unsupervised setting. Our model learns the high-level action co-occurrence and temporal …
unsupervised setting. Our model learns the high-level action co-occurrence and temporal …
Discriminative multi-instance multitask learning for 3D action recognition
As the prosperity of low-cost and easy-operating depth cameras, skeleton-based human
action recognition has been extensively studied recently. However, most of the existing …
action recognition has been extensively studied recently. However, most of the existing …
Latent max-margin multitask learning with skelets for 3-D action recognition
Recent emergence of low-cost and easy-operating depth cameras has reinvigorated the
research in skeleton-based human action recognition. However, most existing approaches …
research in skeleton-based human action recognition. However, most existing approaches …
Robust least squares twin support vector machine for human activity recognition
Human activity recognition is an active area of research in Computer Vision. One of the
challenges of activity recognition system is the presence of noise between related activity …
challenges of activity recognition system is the presence of noise between related activity …
Complex Network-based features extraction in RGB-D human action recognition
A Barkoky, NM Charkari - Journal of Visual Communication and Image …, 2022 - Elsevier
Abstract Analysis of human behavior through visual information has been one of the active
research areas in computer vision community during the last decade. Vision-based human …
research areas in computer vision community during the last decade. Vision-based human …
Category-level 6d object pose recovery in depth images
Intra-class variations, distribution shifts among source and target domains are the major
challenges of category-level tasks. In this study, we address category-level full 6D object …
challenges of category-level tasks. In this study, we address category-level full 6D object …
Watch-n-patch: unsupervised learning of actions and relations
There is a large variation in the activities that humans perform in their everyday lives. We
consider modeling these composite human activities which comprises multiple basic level …
consider modeling these composite human activities which comprises multiple basic level …