In this paper, we address the task of tracking groups of people in surveillance scenarios. This is a major challenge in computer vision, since groups are structured entities, subjected to repeated split and merge events. Our solution is a joint individual-group tracking framework, inspired by a recent technique dubbed decentralized particle filtering. The proposed strategy factorizes the joint individual-group state space in two dependent subspaces where individuals and groups share the knowledge of the joint individual-group distribution. In practice, we establish a tight relation of mutual support between the modeling of individuals and that of groups, promoting the idea that groups are better tracked if individuals are considered, and viceversa. Extensive experiments on a published and novel dataset validate our intuition, opening up to many future developments.

Decentralized particle filter for joint individual-group tracking

BAZZANI, Loris;CRISTANI, Marco;MURINO, Vittorio
2012

Abstract

In this paper, we address the task of tracking groups of people in surveillance scenarios. This is a major challenge in computer vision, since groups are structured entities, subjected to repeated split and merge events. Our solution is a joint individual-group tracking framework, inspired by a recent technique dubbed decentralized particle filtering. The proposed strategy factorizes the joint individual-group state space in two dependent subspaces where individuals and groups share the knowledge of the joint individual-group distribution. In practice, we establish a tight relation of mutual support between the modeling of individuals and that of groups, promoting the idea that groups are better tracked if individuals are considered, and viceversa. Extensive experiments on a published and novel dataset validate our intuition, opening up to many future developments.
9781467312271
Tracking; Groups; Particle Filter
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/11562/471964
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 66
  • ???jsp.display-item.citation.isi??? 40
social impact