In this paper we propose a system for human action tracking and recognition using a robust particle filter-based visual tracker and a novel descriptor, to represent spatio-temporal interest points, based on an effective combination of a new 3D gradient descriptor with an optic flow descriptor. These points are used to represent video sequences using a bag of spatio-temporal visual words, following the successful results achieved in object and scene classification. The tracker assigns the points to each individual in a scene, allowing the classification of the action performed by each person. The system has been extensively tested on the standard KTH and Weizmann actions datasets, as well as on real world surveillance videos.

Human Action Recognition and Localization using Spatio-temporal Descriptors and Tracking / L. Ballan;M. Bertini;A. Del Bimbo;L. Seidenari;G. Serra. - ELETTRONICO. - (2009), pp. 1-8. (Intervento presentato al convegno AI*IA International Workshop on Pattern Recognition and Artificial Intelligence for Human Behaviour Analysis (PRAI*HBA) nel 2009-Dec).

Human Action Recognition and Localization using Spatio-temporal Descriptors and Tracking

L. Ballan;M. Bertini;A. Del Bimbo;L. Seidenari;G. Serra
2009

Abstract

In this paper we propose a system for human action tracking and recognition using a robust particle filter-based visual tracker and a novel descriptor, to represent spatio-temporal interest points, based on an effective combination of a new 3D gradient descriptor with an optic flow descriptor. These points are used to represent video sequences using a bag of spatio-temporal visual words, following the successful results achieved in object and scene classification. The tracker assigns the points to each individual in a scene, allowing the classification of the action performed by each person. The system has been extensively tested on the standard KTH and Weizmann actions datasets, as well as on real world surveillance videos.
2009
Proc. of AI*IA International Workshop on Pattern Recognition and Artificial Intelligence for Human Behaviour Analysis (PRAI*HBA)
AI*IA International Workshop on Pattern Recognition and Artificial Intelligence for Human Behaviour Analysis (PRAI*HBA)
2009-Dec
L. Ballan;M. Bertini;A. Del Bimbo;L. Seidenari;G. Serra
File in questo prodotto:
File Dimensione Formato  
prai-hba09.pdf

Accesso chiuso

Tipologia: Pdf editoriale (Version of record)
Licenza: Tutti i diritti riservati
Dimensione 1.57 MB
Formato Adobe PDF
1.57 MB Adobe PDF   Richiedi una copia

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/368176
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact