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Location-Based Saliency Maps from a Fully Connected Layer using Multi-Shapes

Authors
Kim, HoseungHan, Seong-SooJeong, Chang-Sung
Issue Date
31-1월-2021
Publisher
KSII-KOR SOC INTERNET INFORMATION
Keywords
Saliency Map; Contrast; Fully Connected Layer; Multi Shape; Location-Based Normalization
Citation
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, v.15, no.1, pp.166 - 179
Indexed
SCIE
SCOPUS
KCI
Journal Title
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
Volume
15
Number
1
Start Page
166
End Page
179
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/129338
DOI
10.3837/tiis.2021.01.010
ISSN
1976-7277
Abstract
Recently, with the development of technology, computer vision research based on the human visual system has been actively conducted. Saliency maps have been used to highlight areas that are visually interesting within the image, but they can suffer from low performance due to external factors, such as an indistinct background or light source. In this study, existing color, brightness, and contrast feature maps are subjected to multiple shape and orientation filters and then connected to a fully connected layer to determine pixel intensities within the image based on location-based weights. The proposed method demonstrates better performance in separating the background from the area of interest in terms of color and brightness in the presence of external elements and noise. Location-based weight normalization is also effective in removing pixels with high intensity that are outside of the image or in non-interest regions. Our proposed method also demonstrates that multi-filter normalization can be processed faster using parallel processing.
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Jeong, Chang Sung
공과대학 (전기전자공학부)
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