Human Action Recognition Based on Body ...
Document type :
Communication dans un congrès avec actes
Title :
Human Action Recognition Based on Body Segmentation Models
Author(s) :
Huyghe, Catherine [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ihaddadene, Nacim [Auteur]
Haessle, Thomas [Auteur]
Djeraba, Chaabane [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ihaddadene, Nacim [Auteur]
Haessle, Thomas [Auteur]
Djeraba, Chaabane [Auteur]
Conference title :
CBMI
City :
Lille
Country :
France
Start date of the conference :
2021-06-28
Book title :
2021 International Conference on Content-Based Multimedia Indexing (CBMI)
English keyword(s) :
Actions recognition
smart surveillance
ambient assisted living
smart surveillance
ambient assisted living
HAL domain(s) :
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
English abstract : [en]
Human action recognition in videos is an important issue in computer vision. We propose an approach based on the integration of partial or global human body segmentation in the classification process to deal with partial ...
Show more >Human action recognition in videos is an important issue in computer vision. We propose an approach based on the integration of partial or global human body segmentation in the classification process to deal with partial movements and immobility. Experimentation on UCF101 public dataset output competitive recognition accuracy related state of the art.Show less >
Show more >Human action recognition in videos is an important issue in computer vision. We propose an approach based on the integration of partial or global human body segmentation in the classification process to deal with partial movements and immobility. Experimentation on UCF101 public dataset output competitive recognition accuracy related state of the art.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
Files
- https://hal.archives-ouvertes.fr/hal-03265627/document
- Open access
- Access the document
- https://hal.archives-ouvertes.fr/hal-03265627/document
- Open access
- Access the document
- https://hal.archives-ouvertes.fr/hal-03265627/document
- Open access
- Access the document
- document
- Open access
- Access the document
- CBMI2021.pdf
- Open access
- Access the document