Action recognition in videos is a relevant and challenging task of automatic semantic video analysis. Most successful approaches exploit local space-time descriptors. These descriptors are usually carefully engineered in order to obtain feature invariance to photometric and geometric variations. The main drawback of space-time descriptors is high dimensionality and efficiency. In this paper we propose a novel descriptor based on 3D Zernike moments computed for space-time patches. Moments are by construction not redundant and therefore optimal for compactness. Given the hierarchical structure of our descriptor we propose a novel similarity procedure that exploits this structure comparing features as pyramids. The approach is tested on a public dataset and compared with state-of-the art descriptors.

Space-time Zernike Moments and Pyramid Kernel Descriptors for Action Classification / L., Costantini; L., Seidenari; Serra, Giuseppe; A., Del Bimbo; L., Capodiferro. - STAMPA. - 6979:(2011), pp. 199-208. ((Intervento presentato al convegno International Conference on Image Analysis and Processing tenutosi a Ravenna nel 2011-September.

Space-time Zernike Moments and Pyramid Kernel Descriptors for Action Classification

SERRA, GIUSEPPE;
2011

Abstract

Action recognition in videos is a relevant and challenging task of automatic semantic video analysis. Most successful approaches exploit local space-time descriptors. These descriptors are usually carefully engineered in order to obtain feature invariance to photometric and geometric variations. The main drawback of space-time descriptors is high dimensionality and efficiency. In this paper we propose a novel descriptor based on 3D Zernike moments computed for space-time patches. Moments are by construction not redundant and therefore optimal for compactness. Given the hierarchical structure of our descriptor we propose a novel similarity procedure that exploits this structure comparing features as pyramids. The approach is tested on a public dataset and compared with state-of-the art descriptors.
International Conference on Image Analysis and Processing
Ravenna
2011-September
6979
199
208
L., Costantini; L., Seidenari; Serra, Giuseppe; A., Del Bimbo; L., Capodiferro
Space-time Zernike Moments and Pyramid Kernel Descriptors for Action Classification / L., Costantini; L., Seidenari; Serra, Giuseppe; A., Del Bimbo; L., Capodiferro. - STAMPA. - 6979:(2011), pp. 199-208. ((Intervento presentato al convegno International Conference on Image Analysis and Processing tenutosi a Ravenna nel 2011-September.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/979940
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 13
  • ???jsp.display-item.citation.isi??? 7
social impact