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A Visual Saliency Detection Approach by Fusing Low-Level Priors With High-Level Priors

A Visual Saliency Detection Approach by Fusing Low-Level Priors With High-Level Priors

Monika Singh, Anand Singh Singh Jalal, Ruchira Manke, Amir Khan
Copyright: © 2019 |Volume: 9 |Issue: 3 |Pages: 15
ISSN: 2155-6997|EISSN: 2155-6989|EISBN13: 9781522567202|DOI: 10.4018/IJCVIP.2019070102
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MLA

Singh, Monika, et al. "A Visual Saliency Detection Approach by Fusing Low-Level Priors With High-Level Priors." IJCVIP vol.9, no.3 2019: pp.23-37. http://doi.org/10.4018/IJCVIP.2019070102

APA

Singh, M., Jalal, A. S., Manke, R., & Khan, A. (2019). A Visual Saliency Detection Approach by Fusing Low-Level Priors With High-Level Priors. International Journal of Computer Vision and Image Processing (IJCVIP), 9(3), 23-37. http://doi.org/10.4018/IJCVIP.2019070102

Chicago

Singh, Monika, et al. "A Visual Saliency Detection Approach by Fusing Low-Level Priors With High-Level Priors," International Journal of Computer Vision and Image Processing (IJCVIP) 9, no.3: 23-37. http://doi.org/10.4018/IJCVIP.2019070102

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Abstract

Saliency detection has always been a challenging and interesting research area for researchers. The existing methodologies either focus on foreground regions or background regions of an image by computing low-level features. However, considering only low-level features did not produce worthy results. In this paper, low-level features, which are extracted using super pixels, are embodied with high-level priors. The background features are assumed as the low-level prior due to the similarity in the background areas and boundary of an image which are interconnected and have minimum distance in between them. High-level priors such as location, color, and semantic prior are incorporated with low-level prior to spotlight the salient area in the image. The experimental results illustrate that the proposed approach outperform the sate-of-the-art methods.

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