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Salient region detection using high level feature

Zhong Liu, Weihai Chen, Xingming Wu

Year
2014
Citations
2

Abstract

In the last few decades, selective visual attention has been extensively studied for its promising contributions to computer vision applications. Many different models have been proposed to compute visual saliency, which can be coarsely formulated as computational or psychophysical. Most existing methods are based on bottom-up mechanism, an automatic human behavior to guide gaze allocation. And low level features such as color, intensity and orientation are commonly adopted to compute saliency map. In this work, we propose a saliency computation method that integrates high-level information of object with low-level features. The result map is more suitable for most top-down tasks in the field of mobile robot requiring object information.

Keywords

Computer scienceArtificial intelligenceSalientComputer visionGazeOrientation (vector space)Mobile robotFeature (linguistics)Object (grammar)Computation

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