Image saliency detection method based on multifeature maps fusion

Xiaoli Li; Yunpeng Liu; Huaici Zhao

doi:10.1117/12.3045835

9 October 2024 Image saliency detection method based on multifeature maps fusion

Xiaoli Li, Yunpeng Liu, Huaici Zhao

Author Affiliations +

Proceedings Volume 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024); 1328810 (2024) https://doi.org/10.1117/12.3045835
Event: Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 2024, Chengdu, China

Abstract

In this research, we introduce an innovative saliency detection algorithm, comprising three essential steps. Firstly, leveraging fully convolutional networks with aggregation interaction modules, we generate an initial saliency map. Secondly, we extract hand-craft and deep features to express the image, then use manifold ranking method to construct saliency maps. Ultimately, by integrating the outcomes from preceding stages, we generate the final saliency map. Experimental findings demonstrate that our method surpasses twelve cutting-edge saliency detection techniques in terms of precision, recall, F-measure, and MAE value metrics."

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Xiaoli Li, Yunpeng Liu, and Huaici Zhao "Image saliency detection method based on multifeature maps fusion", Proc. SPIE 13288, Fourth International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2024), 1328810 (9 October 2024); https://doi.org/10.1117/12.3045835

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KEYWORDS

Feature extraction

Image fusion

Visualization

Detection and tracking algorithms

Feature fusion

Image segmentation

Matrices

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