| Summary: | 碩士 === 淡江大學 === 土木工程學系 === 85 === In this thesis, we try to use image processing technique to
count pedestrians which are stationary in the image and track
their trajectories when they are walking. In the pedestrian
counting system, since the pixels which pedestrian possesses in
the image are directly proportional to number of pedestrians, so
we use background differencing method to establish regression
model and calculate all people in the image. On the other hand,
we use interframe differencing method to establish another
regression model which is used to calculate moving pedestrians
in the image. The difference between total number of pedestrians
and number of moving pedestrians at the same time is considered
to be the number of stationary pedestrians in the image. About
pedestrian''s trajectory detection, we adopt template matching
method based on image feature invariants to track each
pedestrian''s template in sequence images. After linking every
coordinates, we obtain pedestrians'' trajectory lines.
The detection system can output four important parameters
including pedestrians'' number, trajectories, speeds, and
directions. A case study was demonstrated. About stationary
pedestrians, the absolute diffenence between automaticcounts and
real counts for each image is almost within 2 persons, and the
ratio of maximum absolute error to the real count decrease
gradually when people increase. About trajectory, the use of
template matching method have only an average error of 1 pixel
in x-axis, 2 pixel in y-axis. The error of speed is about 9.43%.
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