Please use this identifier to cite or link to this item: https://doi.org/10.1007/s00138-011-0372-6
Title: Bottom-up saliency detection for attention determination
Authors: Ge, S.S. 
He, H.
Zhang, Z.
Keywords: Color sensitivity
Graph cuts
Informational entropy
Saliency
Social robot
Issue Date: Jan-2013
Source: Ge, S.S., He, H., Zhang, Z. (2013-01). Bottom-up saliency detection for attention determination. Machine Vision and Applications 24 (1) : 103-116. ScholarBank@NUS Repository. https://doi.org/10.1007/s00138-011-0372-6
Abstract: In this paper, the technique of saliency detection is proposed to model people's biological ability of attending to their interest. There are two phases in the scheme of intelligent saliency searching: saliency filtering and saliency refinement. In saliency filtering, non-salient regions of a scene image are filtered out by measuring information entropy and biological color sensitivity. The information entropy evaluates the level of knowledge and energy contained, and the color sensitivity measures biological stimulation of a presented scene. In saliency refinement, candidate salient regions obtained are cultivated for a good representation of saliency by extracting salient objects, similarly to people's manner of perception. The performance of the proposed technique is studied on noiseless and noisy natural scenes and evaluated with eye fixation data. The evaluation proved the effectiveness of the approach in discovering salient regions or objects from scene images. The performance of addressing transformation and illumination variance is also investigated. © 2011 Springer-Verlag.
Source Title: Machine Vision and Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/55222
ISSN: 09328092
DOI: 10.1007/s00138-011-0372-6
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