@inproceedings{1418a7c8475044028b67ffbf6e5b0a2e,
title = "Detection of saliency map as image feature outliers using random projections based method",
abstract = "We describe a novel method based on Random Projections for construction of image saliency maps. The method identifies outliers in the 2D projections of image point features as salient image points using Random Projections and kernel density estimation. We compare the method with other known methods in the area and validated on a number of benchmark images. The robustness of the method when Gaussian blurring is applied to an image is demonstrated and evaluated using F-statistics of several image quality metrics. Application of the proposed method for image processing is discussed.",
keywords = "Random Projections, image processing, saliency",
author = "Robertas Dama{\v s}evi{\v c}ius and Rytis Maskeliunas and Marcin Wo{\'z}niak and Dawid Po{\l}ap and Tatjana Sidekerskiene and Marcin Gabryel",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 13th International Computer Engineering Conference, ICENCO 2017 ; Conference date: 27-12-2017 Through 28-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/ICENCO.2017.8289768",
language = "English",
series = "ICENCO 2017 - 13th International Computer Engineering Conference: Boundless Smart Societies",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "85--90",
booktitle = "ICENCO 2017 - 13th International Computer Engineering Conference",
address = "United States",
}