Weighted Incremental Subspace Learning
نویسندگان
چکیده
In a cognitive vision system, learning is expected to be a continuous process, which treats input images and pixels selectively. In this paper we present a method for subspace learning, which takes these considerations into account. First, we present a generalized PCA approach, which estimates the principal subspace considering weighted pixels and images. Next, we propose a method for incremental learning, which sequentially updates the principal subspace. Finally, we combine these two techniques into a unified method for weighted incremental subspace learning.
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تاریخ انتشار 2002