A Novel Region-Based Image Retrieval Algorithm Using Selective Visual Attention Model

Feng, Songhe; Xu, De; Yang, Xu; Aimin, Wu

doi:10.1007/11558484_30

Cited by 4 publications

(1 citation statement)

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“…Saliency map is a two-dimensional distribution of the image visual attention region, the bigger gray value is, the more significant the region is, the more attention it causes. [8], which belongs to computing paradigm of "center around contrast among scales, and interpolation fusion among scales"; the second is space-based algorithm named Itti [9], put forward by Itti L, Koch C, etc; Itti's algorithm is used to achieve the extraction of the saliency region of road in this article.…”

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confidence: 99%

The Application of Visual Attention Mechanism in Road Disaster Identification and early Warning System

Hua

Xiao

2013

AMM

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Visual attention mechanism is introduced into the traditional road disaster monitoring and early warning system. In this system, the disaster region is the focus of attention (FOA), which happens to be the object needed to process. Ittis algorithm [1]was used to extract the saliency map, then quickly located the regions which may contain disaster according to saliency. The recognition and early warning of disaster can be completed, quickly. This method was tested snowstorms and rolling stones are simulated, and gave the corresponding experimental results. Experiment results show the correctness and efficiency of introducing visual attention mechanism into road disaster monitor and early warning system. It is of great significance and practical value for reducing the computation and improving real-time performance of the total system.

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confidence: 99%