The problem of image matching and target tracking based on singular value decomposition (SVD) is discussed. The SVD
has robust performance that is invariant to image disturbance and it makes the singular value credible to represent the
image as an algebraic feature. A template-updating strategy is proposed to update the current template based on the scale
invariant character of the singular value vector. The updated template that contains the accurate target is adaptively
acquired according to the singular value's scale invariance. Experiments are performed on a large test set and the results
show that the proposed strategy is practical and efficient in target tracking.
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