40 citations · 68 across the 4 of their papers we have counts for
6 papers · 1 filter
Video-based Human Action Recognition using Deep Learning: A Review
Hieu H. Pham, Louahdi Khoudour, Alain Crouzil +2
Human action recognition is an important application domain in computer vision. Its primary aim is to accurately describe human actions and their interactions from a previously uns…
A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera
Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour +3
We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from RGB video sequences. Our approach proceeds along two stages. In…
A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data
Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour +3
We present a new deep learning approach for real-time 3D human action recognition from skeletal data and apply it to develop a vision-based intelligent surveillance system. Given a…
Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks
Huy-Hieu Pham, Louahdi Khoudour, Alain Crouzil +2
Recognizing human actions in untrimmed videos is an important challenging task. An effective 3D motion representation and a powerful learning model are two key factors influencing…
Skeletal Movement to Color Map: A Novel Representation for 3D Action Recognition with Inception Residual Networks
Huy Hieu Pham, Louahdi Khoudour, Alain Crouzil +2
We propose a novel skeleton-based representation for 3D action recognition in videos using Deep Convolutional Neural Networks (D-CNNs). Two key issues have been addressed: First, h…
Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks
Huy-Hieu Pham, Louahdi Khoudour, Alain Crouzil +2
Automatic human action recognition is indispensable for almost artificial intelligent systems such as video surveillance, human-computer interfaces, video retrieval, etc. Despite a…