标题:A brief survey of visual saliency detection
作者:Ullah I.; Jian M.; Hussain S.; Guo J.; Yu H.; Wang X.; Yin Y.
作者机构:[Ullah, I] School of Software Engineering, Shandong University, Jinan, China;[ Jian, M] School of Information Science and Engineering, Linyi Universit 更多
通讯作者:Yin, Y(ylyin@sdu.edu.cn)
通讯作者地址:[Yin, Y] School of Software Engineering, Shandong UniversityChina;
来源:Multimedia Tools and Applications
出版年:2020
DOI:10.1007/s11042-020-08849-y
关键词:Saliency detection; Saliency model; Salient object; Visual cues
摘要:Salient object detection models mimic the behavior of human beings and capture the most salient region/object from the images or scenes, this field contains many important applications in both computer vision and pattern recognition tasks. Despite hundreds of models that have been proposed in this field, but still, it requires a large room for research. This paper demonstrates a detailed overview of the recent progress of saliency detection models in terms of heuristic-based techniques and deep learning-based techniques. we have discussed and reviewed its co-related fields, such as Eye-fixation-prediction, RGBD salient-object-detection, co-saliency object detection, and video-saliency-detection models. We have reviewed the key issues of the current saliency models and discussed future trends and recommendations. The broadly utilized datasets and assessment strategies are additionally investigated in this paper. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
收录类别:SCOPUS
Scopus被引频次:1
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083841578&doi=10.1007%2fs11042-020-08849-y&partnerID=40&md5=b723361450aeb427ee92547680971164
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