710 research outputs found
Robust Multi-Person Tracking from Moving Platforms
In this paper, we address the problem of multi-person tracking in busy pedestrian
zones, using a stereo rig mounted on a mobile platform. The
complexity of the problem calls for an integrated solution, which
extracts as much visual information as possible and combines it
through cognitive feedback. We propose such an approach, which
jointly estimates camera position, stereo depth, object detection,
and tracking. We model the interplay between these components
using a graphical model. Since the model has to
incorporate object-object interactions, and temporal links to past
frames, direct inference is intractable. We therefore propose a two-stage
procedure: for each frame we first solve a simplified version of the
model (disregarding interactions and temporal continuity) to
estimate the scene geometry and an overcomplete set of object
detections. Conditioned on these results, we then address object
interactions, tracking, and prediction in a second step. The
approach is experimentally evaluated on several long and difficult
video sequences from busy inner-city locations. Our results show
that the proposed integration makes it possible to deliver stable
tracking performance in scenes of realistic complexity
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