Relation of Descriptor Completeness and Distinctiveness to Localization of the Most Informative Regions in Images

Kalinin, Konstantin; Petrushan, Mikhail; Samarin, Anatoly

doi:10.1177/0301006615594929

Cited by 1 publication

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“…All of them are then combined in a final map. Kalinin et al [45] approached the problem of localization of the most informative regions in images checking the similarity of those regions with the response of foveal filters. In cognitive top-down approaches like those proposed in [10] and [46], the visual attention process is considered task-dependent.…”

Section: ) Traditional Approaches-based Saliency Detectionmentioning

confidence: 99%

A Multi-Scale Colour and Keypoint Density-Based Approach for Visual Saliency Detection

et al. 2020

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In the first seconds of observation of an image, several visual attention processes are involved in the identification of the visual targets that pop-out from the scene to our eyes. Saliency is the quality that makes certain regions of an image stand out from the visual field and grab our attention. Saliency detection models, inspired by visual cortex mechanisms, employ both colour and luminance features. Furthermore, both locations of pixels and presence of objects influence the Visual Attention processes. In this paper, we propose a new saliency method based on the combination of the distribution of interest points in the image with multiscale analysis, a centre bias module and a machine learning approach. We use perceptually uniform colour spaces to study how colour impacts on the extraction of saliency. To investigate eye-movements and assess the performances of saliency methods over object-based images, we conduct experimental sessions on our dataset ETTO (Eye Tracking Through Objects). Experiments show our approach to be accurate in the detection of saliency concerning state-of-the-art methods and accessible eye-movement datasets. The performances over object-based images are excellent and consistent on generic pictures. Besides, our work reveals interesting findings on some relationships between saliency and perceptually uniform colour spaces.

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Section: ) Traditional Approaches-based Saliency Detectionmentioning

confidence: 99%