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- W1993428035 abstract "This paper presents a new approach to using locally linear embedding (LLE) method in object tracking problems. By means of measuring the divergence of the K nearest neighbors of test data, a novel method is proposed to distinguish object from background directly through the LLE embedding results. Avoiding training a mapping function, this approach is less dependent on a beforehand training set of object compare to other attempts of utilizing manifold embedding method on object tracking. Besides, an asymmetric version of LLE is derived to improve the tracking performance. A Bayesian inference framework is built to apply this approach to visual tracking problem using particle filter. Experimental results demonstrate both efficiency and adaptability of our algorithm." @default.
- W1993428035 created "2016-06-24" @default.
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- W1993428035 date "2010-10-01" @default.
- W1993428035 modified "2023-09-25" @default.
- W1993428035 title "A new approach to object tracking using local linear embedding method" @default.
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- W1993428035 doi "https://doi.org/10.1109/cisp.2010.5648262" @default.
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