亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Automatic Extraction and Linkage between Textual and Spatial Data for Architectural Heritage

计算机科学 功能可见性 过程(计算) 空间分析 人机交互 情报检索 地理 遥感 操作系统
作者
Sun-Young Jang,Sung-Ah Kim
出处
期刊:Journal on computing and cultural heritage [Association for Computing Machinery]
卷期号:16 (3): 1-19 被引量:1
标识
DOI:10.1145/3586158
摘要

Recent developments in experience technologies such as augmented reality (AR)/virtual reality (VR) have facilitated receiving content about the audience on site and experiencing architectural heritage in a virtual space. Despite the development of experience devices, if the quantity and quality of content are not sufficiently supported, then immersive user experiences are bound to be limited. Considerable amounts of money, manpower, and time are required to make a building into experience content. Tasks such as building a database create experiential content that occupies a large proportion of the overall process. Therefore, it is necessary to devise an automated method for building data, which is the basis for content creation. This study extracted data on architectural heritage automatically and structured it around spatial expression so it can function as base work for mass content creation. Specifically, this study devised a method to link and structure text and spatial data centering on the architectural spatial data model. Text and spatial data were extracted automatically using deep learning, and each derived result was mapped to Indoor Affordance Spaces—an indoor spatial data model—to test whether information inference is possible based on the interconnection relationship. The spatial experience route inferred using the data model expresses the detailed area where the viewing element exists, based on the description method of the model. It also shows the process of reconstructing an efficient movement line with topological relationships between spaces. The series of processes presented herein showed sufficient applicability to the extraction of data and the connection and utilization of data models. This is useful for extracting and classifying information used for content from massive raw data. This study also considered the specificity arising from architectural heritage and spatial information. Therefore, the research concept can be applied in exhibition and experience spaces, such as architectural heritage, museums, and art galleries, to create sources for content creation and refer to content composition.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI6.4应助Shiku采纳,获得10
8秒前
25秒前
香蕉觅云应助Efaith采纳,获得10
29秒前
义气凝阳发布了新的文献求助50
29秒前
134345发布了新的文献求助10
34秒前
1分钟前
查查完成签到,获得积分10
1分钟前
Kao应助科研通管家采纳,获得10
1分钟前
查查发布了新的文献求助10
1分钟前
CodeCraft应助MZ采纳,获得10
1分钟前
顾矜应助查查采纳,获得10
1分钟前
1分钟前
MZ发布了新的文献求助10
1分钟前
2分钟前
Efaith发布了新的文献求助10
2分钟前
2分钟前
tangzhidi发布了新的文献求助10
2分钟前
万能图书馆应助MZ采纳,获得10
2分钟前
2分钟前
MZ发布了新的文献求助10
2分钟前
MchemG完成签到,获得积分0
3分钟前
屎侬完成签到,获得积分20
3分钟前
Criminology34应助科研通管家采纳,获得30
3分钟前
Criminology34应助科研通管家采纳,获得30
3分钟前
3分钟前
Shiku发布了新的文献求助10
3分钟前
脑洞疼应助结实的博超采纳,获得10
4分钟前
义气凝阳发布了新的文献求助10
4分钟前
NexusExplorer应助MZ采纳,获得10
4分钟前
cube半肥半瘦完成签到,获得积分10
4分钟前
4分钟前
4分钟前
MZ发布了新的文献求助10
4分钟前
4分钟前
科研通AI6.4应助义气凝阳采纳,获得10
5分钟前
5分钟前
5分钟前
Zephyr完成签到 ,获得积分10
6分钟前
szx233完成签到 ,获得积分10
6分钟前
油菜花完成签到 ,获得积分10
6分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Nondestructive Testing Handbook: Vol. 4, Thermal and Infrared Testing (IR), 4th ed 800
作者名:Kristopher P. Plain,悉尼大学的,目前只能查到其四篇论文,想找到其博士论文 590
Évora na Idade Média 555
Soil mites of the family Rhagidiidae (Actinedida: Eupodoidea). Morphology, Systematics, Ecology 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Radical Reactions 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7354917
求助须知:如何正确求助?哪些是违规求助? 8965818
关于积分的说明 19048361
捐赠科研通 7003023
什么是DOI,文献DOI怎么找? 3222075
关于科研通互助平台的介绍 2386272
邀请新用户注册赠送积分活动 2202659