Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Souhila Kahlouche"'
Autor:
Souhila Kahlouche, Mahmoud Belhocine
Publikováno v:
Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics.
Publikováno v:
International Journal of Computational Intelligence and Applications. 20
In this work, efficient human activity recognition (HAR) algorithm based on deep learning architecture is proposed to classify activities into seven different classes. In order to learn spatial and temporal features from only 3D skeleton data capture
Autor:
Mahmoud Belhocine, Souhila Kahlouche
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789811564024
In this work, we address the problem of Human Activity Recognition (HAR), applied to service robot. In addition, a real time HRI system able to understand some common interactive human activities is designed. To classify activities into different cla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::498e400249205e57763b4a73dd75b886
https://doi.org/10.1007/978-981-15-6403-1_78
https://doi.org/10.1007/978-981-15-6403-1_78
Publikováno v:
2016 8th International Conference on Modelling, Identification and Control (ICMIC).
In this work, we address the problem of human body pose recognition using RGB-D sensor, to perform user tracking by a mobile robot. User's skeleton joints orientations are used in this approach to compute torso joint orientation, which is necessary t
Publikováno v:
2016 8th International Conference on Modelling, Identification and Control (ICMIC).
The biggest challenges in modern robotics is service robots, which are able to execute many tasks for humans in their presence. This perspective naturally causes the problem of social navigation of mobile robots as well as human-robot interaction. In
Autor:
Souhila, Kahlouche, Karim, Achour
Publikováno v:
International Journal of Advanced Robotic Systems; Mar2007, Vol. 4 Issue 1, p13-16, 4p, 7 Color Photographs, 3 Black and White Photographs, 2 Diagrams, 1 Graph