580,002 research outputs found
Minimal time problem for discrete crowd models with a localized vector field
In this work, we study the minimal time to steer a given crowd to a desired
configuration. The control is a vector field, representing a perturbation of
the crowd velocity, localized on a fixed control set. We characterize the
minimal time for a discrete crowd model, both for exact and approximate
controllability. This leads to an algorithm that computes the control and the
minimal time. We finally present a numerical simulation
Ambient Sound Helps: Audiovisual Crowd Counting in Extreme Conditions
Visual crowd counting has been recently studied as a way to enable people
counting in crowd scenes from images. Albeit successful, vision-based crowd
counting approaches could fail to capture informative features in extreme
conditions, e.g., imaging at night and occlusion. In this work, we introduce a
novel task of audiovisual crowd counting, in which visual and auditory
information are integrated for counting purposes. We collect a large-scale
benchmark, named auDiovISual Crowd cOunting (DISCO) dataset, consisting of
1,935 images and the corresponding audio clips, and 170,270 annotated
instances. In order to fuse the two modalities, we make use of a linear
feature-wise fusion module that carries out an affine transformation on visual
and auditory features. Finally, we conduct extensive experiments using the
proposed dataset and approach. Experimental results show that introducing
auditory information can benefit crowd counting under different illumination,
noise, and occlusion conditions. The dataset and code will be released. Code
and data have been made availabl
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