An Attention Module for Object Detection in Cluttered Images

Michela Lecca

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 proposed strategy has been tested on two public real-world image databases showing good performances and it has been applied to the SIFT recognition algorithm.

Keywords

Object Description and Recognition; Scene Understanding; Features and Image Descriptors; Invariances in Recognition

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