ALBERT

Description:    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. Content Type Journal Article Category Original Paper Pages 1-14 DOI 10.1007/s00138-011-0372-6 Authors Shuzhi Sam Ge, Social Robotics Lab, Interactive Digital Media Institute and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576 Singapore Hongsheng He, Social Robotics Lab, Interactive Digital Media Institute and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576 Singapore Zhengchen Zhang, Social Robotics Lab, Interactive Digital Media Institute and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576 Singapore Journal Machine Vision and Applications Online ISSN 1432-1769 Print ISSN 0932-8092