In this paper we investigate the potential of a family of efficient filters – the Gray-Code Kernels – for addressing visual saliency estimation guided by motion. Our implementation relies on the use of 3D kernels applied to overlapping blocks of frames and is able to gather meaningful spatio-temporal information with a very light computation. We introduce an attention module that reasons on the use of pooling strategies, combined in an unsupervised way to derive a saliency map highlighting the presence of motion in the scene. In the experiments we show that our method is able to effectively and efficiently identify the portion of the image where the motion is occurring, providing tolerance to a variety of scene conditions.

Exploring the Use of Efficient Projection Kernels for Motion Saliency Estimation

Nicora E.;Noceti N.
2022

Abstract

In this paper we investigate the potential of a family of efficient filters – the Gray-Code Kernels – for addressing visual saliency estimation guided by motion. Our implementation relies on the use of 3D kernels applied to overlapping blocks of frames and is able to gather meaningful spatio-temporal information with a very light computation. We introduce an attention module that reasons on the use of pooling strategies, combined in an unsupervised way to derive a saliency map highlighting the presence of motion in the scene. In the experiments we show that our method is able to effectively and efficiently identify the portion of the image where the motion is occurring, providing tolerance to a variety of scene conditions.
978-3-031-06432-6
978-3-031-06433-3
File in questo prodotto:
Non ci sono file associati a questo prodotto.

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

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/1088066
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact