Unpublished conference/Abstract (Scientific congresses and symposiums)
Deep Learning and Approach for Tracking People’s Movements in a Video
Bornia, Jemai; Frihida, Ali; Debauche, Olivier et al.
2020The 5th International Conference on CLoud Computing and Artificial Intelligence: Technologies and Applications
 

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Abstract :
[en] Everyday, a large amount of data is produced thanks to technological advances in the field of multimedia, associated with the generalization of their use in many applications. The need to keep control over this content, in terms of data analysis, classification, accurate AI (Artificial Intelligence) algorithms are required to perform this task efficiently and quickly. In this article, we propose an approach using deep learning technologies for the analysis of movement in video sequences. The suggested approach uses images from video splitting to detect objects / entities present and store their descriptions in a standard XML file. As result, we provide a Deep Learning algorithm using TensorFlow for tracking motion and animated entities in video sequences.
Disciplines :
Computer science
Author, co-author :
Bornia, Jemai
Frihida, Ali
Debauche, Olivier  ;  Université de Liège - ULiège > Terra
Mahmoudi, Sidi Ahmed
Manneback, Pierre
Language :
English
Title :
Deep Learning and Approach for Tracking People’s Movements in a Video
Publication date :
02 March 2020
Number of pages :
6
Event name :
The 5th International Conference on CLoud Computing and Artificial Intelligence: Technologies and Applications
Event place :
Marrakech, Morocco
Event date :
November 24-26, 2020
Audience :
International
Available on ORBi :
since 05 September 2021

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