In this paper, we propose a visual attention module that automatically detects the regions of an input previously unseen image, which are more likely occupied by a known object. The module can be integrated in many object recognition systems for reducing the image space in which to search the object, and the computational costs. The strategy has been tested on two public real-world image databases showing good performances. Moreover, we measured the usefulness of this selective visual attention by comparing the performances of the SIFT recognition algorithm with and without the proposed attention module.

An Attention Module for Object Detection in Cluttered Images

Lecca, Michela
2009

Abstract

In this paper, we propose a visual attention module that automatically detects the regions of an input previously unseen image, which are more likely occupied by a known object. The module can be integrated in many object recognition systems for reducing the image space in which to search the object, and the computational costs. The strategy has been tested on two public real-world image databases showing good performances. Moreover, we measured the usefulness of this selective visual attention by comparing the performances of the SIFT recognition algorithm with and without the proposed attention module.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/5221
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