Bottom-up visual attention model for still image: A preliminary study

Sri, Winiarti and Prahara, Adhi and Murinto, Murinto (2020) Bottom-up visual attention model for still image: A preliminary study. [Artikel Dosen]

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Abstract

The philosophy of human visual attention is scientifically explained in the
field of cognitive psychology and neuroscience then computationally
modeled in the field of computer science and engineering. Visual attention
models have been applied in computer vision systems such as object
detection, object recognition, image segmentation, image and video
compression, action recognition, visual tracking, and so on. This work
studies bottom-up visual attention, namely human fixation prediction and
salient object detection models. The preliminary study briefly covers from
the biological perspective of visual attention, including visual pathway, the
theory of visual attention, to the computational model of bottom-up visual
attention that generates saliency map. The study compares some models at each stage and observes whether the stage is inspired by biological
architecture, concept, or behavior of human visual attention. From the
study, the use of low-level features, center-surround mechanism, sparse
representation, and higher-level guidance with intrinsic cues dominate the
bottom-up visual attention approaches. The study also highlights the
correlation between bottom-up visual attention and curiosity.

Item Type:	Artikel Dosen
Keyword:	Visual attention Bottom-up attention Saliency map Computer vision Curiosity
Subjects:	Q Science > Q Science (General)
Divisi / Prodi:	Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Informatics Engineering (S1-Teknik Informatika)
Depositing User:	murinto murinto
Date Deposited:	18 Apr 2023 09:49
Last Modified:	23 Sep 2023 06:09
URI:	http://eprints.uad.ac.id/id/eprint/43018

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