Adaptive template-updating strategy based on singular value decomposition

Guogang Wang; Zhijia Zhang; Zelin Shi

doi:10.1117/12.748104

15 November 2007 Adaptive template-updating strategy based on Singular value decomposition

Guogang Wang, Zhijia Zhang, Zelin Shi

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67861A (2007) https://doi.org/10.1117/12.748104
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

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.

Citation Download Citation

Guogang Wang, Zhijia Zhang, and Zelin Shi "Adaptive template-updating strategy based on Singular value decomposition", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861A (15 November 2007); https://doi.org/10.1117/12.748104

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