VEHICLE DETECTION AND TRACKING USING THE
BLOCK
MATCHING ALGORITHM
Luigi Di Stefano DEIS, University of Bologna
Viale Risorgimento 2, 40136 Bologna, Italy
and
Enrico Viarani DEIS, University of Bologna
Viale Risorgimento 2, 40136 Bologna, Italy e-mail
Keywords: Computer Vision, Traffic Monitoring, Vehicle Tracking
Abstract
The paper describes an approach to vehicle detection and tracking fully
based on the Block Matching Algorithm (BMA), which is the motion
estimation
algorithm employed in the MPEG compression standard. BMA partitions the
current frame in small, fixed size blocks and matches them in the
previous
frame in order to estimate blocks displacement (referred to as motion
vectors)
between two successive frames. The detection and tracking approach is
as
follows. BMA provides motion vectors, which are then regularised using
a Vector Median Filter. After the regularisation step, motion vectors
are
grouped based on their adjacency and similarity, and a set of vehicles
is built per singular frame. Finally, the tracking algorithm
establishes
the correspondences between the vehicles detected in each frames of the
sequence, allowing the estimation of their trajectories as well as the
detection of new entries and exits. The tracking algorithm is strongly
based on the BMA. We consider the BMA output as the basic tracking
information
associated with each block and combine this already available
block-level
tracking with the grouping output so as to achieve the tracking of
vehicles.
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