Salient object detection: A survey
Abstract Detecting and segmenting salient objects from natural scenes, often referred to as salient object detection, has attracted great interest in computer vision. While many models have been proposed and several applications have emerged, a deep understanding of achievements and issues remains l...
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doaj-44f9080fc64541e2afbfec56621197562020-11-25T03:52:45ZengSpringerOpenComputational Visual Media2096-04332096-06622019-06-015211715010.1007/s41095-019-0149-9Salient object detection: A surveyAli Borji0Ming-Ming Cheng1Qibin Hou2Huaizu Jiang3Jia Li4MarkableAITKLNDST, College of Computer Science, Nankai UniversityTKLNDST, College of Computer Science, Nankai UniversityUniversity of Massachusetts AmherstState Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang UniversityAbstract Detecting and segmenting salient objects from natural scenes, often referred to as salient object detection, has attracted great interest in computer vision. While many models have been proposed and several applications have emerged, a deep understanding of achievements and issues remains lacking. We aim to provide a comprehensive review of recent progress in salient object detection and situate this field among other closely related areas such as generic scene segmentation, object proposal generation, and saliency for fixation prediction. Covering 228 publications, we survey i) roots, key concepts, and tasks, ii) core techniques and main modeling trends, and iii) datasets and evaluation metrics for salient object detection. We also discuss open problems such as evaluation metrics and dataset bias in model performance, and suggest future research directions.http://link.springer.com/article/10.1007/s41095-019-0149-9salient object detectionsaliencyvisual attentionregions of interest |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ali Borji Ming-Ming Cheng Qibin Hou Huaizu Jiang Jia Li |
spellingShingle |
Ali Borji Ming-Ming Cheng Qibin Hou Huaizu Jiang Jia Li Salient object detection: A survey Computational Visual Media salient object detection saliency visual attention regions of interest |
author_facet |
Ali Borji Ming-Ming Cheng Qibin Hou Huaizu Jiang Jia Li |
author_sort |
Ali Borji |
title |
Salient object detection: A survey |
title_short |
Salient object detection: A survey |
title_full |
Salient object detection: A survey |
title_fullStr |
Salient object detection: A survey |
title_full_unstemmed |
Salient object detection: A survey |
title_sort |
salient object detection: a survey |
publisher |
SpringerOpen |
series |
Computational Visual Media |
issn |
2096-0433 2096-0662 |
publishDate |
2019-06-01 |
description |
Abstract Detecting and segmenting salient objects from natural scenes, often referred to as salient object detection, has attracted great interest in computer vision. While many models have been proposed and several applications have emerged, a deep understanding of achievements and issues remains lacking. We aim to provide a comprehensive review of recent progress in salient object detection and situate this field among other closely related areas such as generic scene segmentation, object proposal generation, and saliency for fixation prediction. Covering 228 publications, we survey i) roots, key concepts, and tasks, ii) core techniques and main modeling trends, and iii) datasets and evaluation metrics for salient object detection. We also discuss open problems such as evaluation metrics and dataset bias in model performance, and suggest future research directions. |
topic |
salient object detection saliency visual attention regions of interest |
url |
http://link.springer.com/article/10.1007/s41095-019-0149-9 |
work_keys_str_mv |
AT aliborji salientobjectdetectionasurvey AT mingmingcheng salientobjectdetectionasurvey AT qibinhou salientobjectdetectionasurvey AT huaizujiang salientobjectdetectionasurvey AT jiali salientobjectdetectionasurvey |
_version_ |
1724481192012546048 |