Put things in correct location: Describing the scene with contextual cues

Xingming Wu, Chenyang Wang, Weihai Chen, Zhong Liu
{"title":"Put things in correct location: Describing the scene with contextual cues","authors":"Xingming Wu, Chenyang Wang, Weihai Chen, Zhong Liu","doi":"10.1109/ICIEA.2015.7334081","DOIUrl":null,"url":null,"abstract":"In this paper, we reviewed the development of scene understanding, specifically focusing on indoor scene understanding and context used in scene understanding. Different from image segmentation, object detection, 3D reconstruction, etc., which only implements a single task, scene understanding is a technology aiming at implementing a holistic scene parsing, that is, acquiring the spatial extent, location and semantic of every object in a scene. Nevertheless, scene understanding doesn't equal to direct accumulation of individual vision tasks. Along with the development of scene understanding, it has formed its own framework. In general, indoor scene understanding is more challenging than outdoor scene understanding, but with the emergence of RGB-D sensors, more and more researchers have focused on indoor scene understanding. Fusing context information to constrain relationship between adjacent pixels and improve accuracy of algorithm is the common sense in the field of scene understanding. There are three kinds of context, namely, pixel based context, region based context and object based context. In this paper, We reviewed these different context respectively.","PeriodicalId":270660,"journal":{"name":"2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEA.2015.7334081","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In this paper, we reviewed the development of scene understanding, specifically focusing on indoor scene understanding and context used in scene understanding. Different from image segmentation, object detection, 3D reconstruction, etc., which only implements a single task, scene understanding is a technology aiming at implementing a holistic scene parsing, that is, acquiring the spatial extent, location and semantic of every object in a scene. Nevertheless, scene understanding doesn't equal to direct accumulation of individual vision tasks. Along with the development of scene understanding, it has formed its own framework. In general, indoor scene understanding is more challenging than outdoor scene understanding, but with the emergence of RGB-D sensors, more and more researchers have focused on indoor scene understanding. Fusing context information to constrain relationship between adjacent pixels and improve accuracy of algorithm is the common sense in the field of scene understanding. There are three kinds of context, namely, pixel based context, region based context and object based context. In this paper, We reviewed these different context respectively.
把东西放在正确的位置:用情境线索描述场景
本文回顾了场景理解的发展,重点介绍了室内场景理解和场景理解中使用的语境。与图像分割、物体检测、三维重建等只实现单一任务不同,场景理解是一种旨在实现整体场景解析的技术,即获取场景中每个物体的空间范围、位置和语义。然而,场景理解并不等于单个视觉任务的直接积累。随着场景理解的发展,它已经形成了自己的框架。一般来说,室内场景理解比室外场景理解更具挑战性,但随着RGB-D传感器的出现,越来越多的研究人员开始关注室内场景理解。融合上下文信息约束相邻像素之间的关系,提高算法的精度是场景理解领域的共识。上下文有三种类型,即基于像素的上下文、基于区域的上下文和基于对象的上下文。在本文中,我们分别回顾了这些不同的背景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信