BMVC 2004, Kingston, 7th-9th Sept, 2004

Multi-Camera Target Tracking in Blind Regions of Cameras with Non-overlapping Fields of View
A. Chilgunde (National University of Singapore), P. Kumar (Institute for
InforComm Research, Singapore), S. Ranganath (University of Singapore)
and H Weimin (Institute for InfoComm Research, Singapore)

In this paper, we propose a real time system for tracking targets across
blind regions of multiple cameras with non-overlapping fields of views (FOVs)
using camera topology, and targets' motion and shape information. Kalman
filters are used to robustly track each target's shape and motion in each camera
view and the common ground plane view composed of all camera views.
The target's track in the blind region between cameras is obtained using
Kalman filter predictions. For multi-camera correspondence matching we
compute the Gaussian distributions of the tracking parameters across cameras
for the target motion and position in the ground plane view. Matching of
targets across camera views uses a graph based track initialization scheme,
which accumulates information from occurrences of target in several consecutive
frames of the video. Probabilistic matching is carried out by using the
track parameters for new tracks obtained from the graph in a camera view
with the parameters of the terminated tracks learnt by Kalman filters in the
other camera views and ground plane view. We obtain 85% accuracy for
corresponding matching while tracking vehicles observed from two cameras
monitoring a highway.
(pdf article)