Visual tracking using particle swarm optimization
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The problem of robust extraction of visual odometry from a sequence of images obtained by an ...
The problem of robust extraction of visual odometry from a sequence of images obtained by an
eye in hand camera configuration is addressed. A novel approach toward solving planar
template based tracking is proposed which performs a non-linear image alignment for
successful retrieval of camera transformations. In order to obtain global optimum a biometaheuristic
is used for optimization of similarity among the planar regions. The proposed
method is validated on image sequences with real as well as synthetic transformations and
found to be resilient to intensity variations. A comparative analysis of the various similarity
measures as well as various state-of-art methods reveal that the algorithm succeeds in tracking
the planar regions robustly and has good potential to be used in real applications.
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