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Model of visual attention for video sequences

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Initial basis images. a) the original image; b) a set of basis functions received by ICA from several patches from one image; c) and d) the convolution results of two functions with the original image.
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Figure 1: Initial basis images. a) the original image; b) a set of basis functions received by ICA from several patches from one image; c) and d) the convolution results of two functions with the original image.

Mentions: The main goal of this work is to use sequences of images and to design an attention model including conjunction search based on unsupervised self-learning. First, Independent Component Analysis algorithm is used to determine an initial set of basis functions from the first image (Figure 1). Second, unsupervised self-organizing learning is used to group together similar bases functions (Figure 2).


Model of visual attention for video sequences
Initial basis images. a) the original image; b) a set of basis functions received by ICA from several patches from one image; c) and d) the convolution results of two functions with the original image.
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Related In: Results  -  Collection

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Figure 1: Initial basis images. a) the original image; b) a set of basis functions received by ICA from several patches from one image; c) and d) the convolution results of two functions with the original image.
Mentions: The main goal of this work is to use sequences of images and to design an attention model including conjunction search based on unsupervised self-learning. First, Independent Component Analysis algorithm is used to determine an initial set of basis functions from the first image (Figure 1). Second, unsupervised self-organizing learning is used to group together similar bases functions (Figure 2).

View Article: PubMed Central - HTML

No MeSH data available.