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Abstract |
Tracking by Image Processing in a Real-Time System
This master's thesis develops an algorithm for tracking of cars robust
enough to handle turning cars. It is implemented in the image
processing environment Image Processing Application Programming
Interface (IPAPI) for use with the WITAS project.
Firstly, algorithms, comparable with one currently used in the
WITAS-project, are studied. The focus is on how rotation, that
originates from the turning of the cars, affects tracking
performance. The algorithms studied all perform an exhaustive search
over a region, close to the last known position of the object being
tracked, to find a match. After this, an iterative algorithm, based on
the idea that a car can only rotate, translate and change scale, is
introduced. The algorithm estimates the parameters describing this
rotation, translation, and change of scale, iteratively.
The iterative process needs a initial parameter estimate that is
accurate enough for the algorithm to converge. The developed algorithm
is based on an earlier publication on the subject, however the
mathematical description, and deduction, of it is taken one step
further than in this publication. The iterative algorithm used
performs well under the assumption that the data used fulfills some
basic criteria. These demands comprises: placement of camera, template
size as well as how the parameters may vary between two
observations. The iterative algorithm is also potentially faster than
exhaustive search methods, because few iterations are needed when the
parameters change slowly. Better initial parameters should improve
stability and speed of convergation. Other suggestions that could give
better performance is discussed, e.g., methods to better extract the
target from the surroundings.
Per Öberg
2003
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Senast uppdaterad: 2021-11-10
