Visual tracking with explicit occlusion models is computationally hard, in the sense that the complexity explodes as the number of targets increases. Recently, the hybrid joint-separable (HJS) model has been proposed that enables tracking the local appearance of a number of bodies through occlusions with a quadratic, no more exponential, upper bound. In this paper we extend that method to account for a larger spectrum of visual interactions, captured by a full-image likelihood enabling true Bayesian inference, without compromising scalability. The resulting tracker then proves to be significantly more robust, and able to resolve long term occlusion among five people aligned on a single line-of-sight, observed from a single camera, at a manageable computational cost.

A HJS Filter to Track Visually Interacting Targets

Lanz, Oswald
2009

Abstract

Visual tracking with explicit occlusion models is computationally hard, in the sense that the complexity explodes as the number of targets increases. Recently, the hybrid joint-separable (HJS) model has been proposed that enables tracking the local appearance of a number of bodies through occlusions with a quadratic, no more exponential, upper bound. In this paper we extend that method to account for a larger spectrum of visual interactions, captured by a full-image likelihood enabling true Bayesian inference, without compromising scalability. The resulting tracker then proves to be significantly more robust, and able to resolve long term occlusion among five people aligned on a single line-of-sight, observed from a single camera, at a manageable computational cost.
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/11582/11208
 Attenzione

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

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