Wrong turn - no dead end: a stochastic pedestrian motion model
S Pellegrini, A Ess, M Tanaskovic and Luc Van Gool
In: International workshop on socially intelligent surveillance and monitoring - SISM 2010, 14 June 2010, San Francisco, USA.
This paper addresses the use of social behavior models
for the prediction of a pedestrian’s future motion. Recently,
such models have been shown to outperform simple
constant velocity models in cases where data association
becomes ambiguous, e.g. in case of occlusion, bad image
quality, or low frame rates. However, to account for
the multiple alternatives a pedestrian can choose from, one
has to go beyond the currently available deterministic models.
To this end, we propose a stochastic extension of a recently
proposed simulation-based motion model. This new
instantiation can cater for the possible behaviors in an entire
scene in a multi-hypothesis approach, using a principled
modeling of uncertainties. In a set of experiments for
prediction and template-based tracking, we compare it to a
deterministic instantiation and investigate the general value
of using an advanced motion prior in tracking.
|EPrint Type:||Conference or Workshop Item (Paper)|
|Project Keyword:||Project Keyword UNSPECIFIED|
|Deposited By:||Luc Van Gool|
|Deposited On:||17 March 2011|