Small public space vitality analysis and evaluation based on human trajectory modeling using video data

活力 弹道 空格(标点符号) 计算机科学 质量(理念) 索引(排版) 人工智能 统计 数学 天文 神学 认识论 操作系统 物理 万维网 哲学
作者
Tong Niu,Linbo Qing,Longmei Han,Ying Long,Jingxuan Hou,Lindong Li,Wang Tang,Qizhi Teng
出处
期刊:Building and Environment [Elsevier BV]
卷期号:225: 109563-109563 被引量:46
标识
DOI:10.1016/j.buildenv.2022.109563
摘要

Small public spaces are important for citizens to live and socialize with a high utilization rate. The vitality of small public space plays an important role in evaluating space quality and attraction and provides reference for urban governance issues such as vitality evaluation of public space, quality optimization, and site micro-renewal. Previous studies of vitality based on low-throughput surveys or big data with low positioning accuracy are not suitable for the high-efficiency study of small public space. In this study, a systematic framework of vitality quantification in small public spaces is built on fine-grained human trajectories extracted from videos for more efficient and refined human-oriented vitality evaluation. A multi-indicator vitality quantification method is first proposed to comprehensively represent human vitality, including number of people, duration of stay, motion speed, trajectory diversity and trajectory complexity. Furthermore, a video dataset of small public space along with our sub-index-assisted expert assessing scheme is proposed to evaluate our vitality quantification framework. Finally, we analyze the correlation between quantitative vitality indicators and the expert-assessing vitality through multiple linear regression and obtain the optimal vitality quantification model. The experimental results indicate that our dataset is reliable and the vitality quantification model constructed with our quantitative indicators can better characterize urban vitality than the previous model based on number of people and staying time.
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
夏夏夏完成签到,获得积分10
1秒前
kjdgahdg发布了新的文献求助10
1秒前
思源的应助被yy采纳,获得10
3秒前
研友_nxwN7L完成签到,获得积分10
3秒前
土豆大魔王完成签到,获得积分10
3秒前
CodeCraft的应助被坦率帅哥采纳,获得10
4秒前
刘广顺发布了新的文献求助10
5秒前
6秒前
7秒前
Ivan完成签到 ,获得积分10
8秒前
9秒前
科研小菜鸡的应助被zsl采纳,获得10
9秒前
10秒前
10秒前
汉堡包的应助被不安的半梦采纳,获得10
11秒前
syf发布了新的文献求助10
11秒前
13秒前
飞利浦发布了新的文献求助10
14秒前
霍巧凡发布了新的文献求助10
15秒前
taekiii发布了新的文献求助10
15秒前
sincoco完成签到,获得积分10
16秒前
17秒前
坦率帅哥发布了新的文献求助10
17秒前
辛木完成签到,获得积分10
17秒前
华仔的应助被syf采纳,获得10
17秒前
19秒前
xin发布了新的文献求助10
19秒前
青年才俊发布了新的文献求助10
20秒前
20秒前
小二郎的应助被辛木采纳,获得10
21秒前
21秒前
zhou默完成签到 ,获得积分10
21秒前
彭于晏的应助被健忘的半青采纳,获得30
22秒前
Joyhold完成签到,获得积分10
22秒前
hhy发布了新的文献求助10
23秒前
23秒前
23秒前
斯文败类的应助被kjdgahdg采纳,获得10
24秒前
科研通AI6.2的应助被kjdgahdg采纳,获得10
24秒前
搜集达人的应助被kjdgahdg采纳,获得10
24秒前
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
自動車の空力技術 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Issues in Task-Based Language Teaching 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 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7783710
求助须知:如何正确求助?哪些是违规求助? 9322987
关于积分的说明 20392570
捐赠科研通 7372332
什么是DOI,文献DOI怎么找? 3320737
关于科研通互助平台的介绍 2468747
邀请新用户注册赠送积分活动 2336971