Automatically Gather Address Specific Dwelling Images Using Google Street View

被引:1
|
作者
Khan, Salman [1 ]
Salvaggio, Carl [1 ]
机构
[1] Rochester Inst Technol, Ctr Imaging Sci, Rochester, NY 14623 USA
关键词
D O I
10.1109/ICPR48806.2021.9413059
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Exciting research is being conducted using Google's street view imagery. Researchers can have access to training data that allows CNN training for topics ranging from assessing neighborhood environments to estimating the age of a building. However, due to the uncontrolled nature of imagery available via Google's Street View API, data collection can be lengthy and tedious. In an effort to help researchers gather address specific dwelling images efficiently, we developed an innovative and novel way of automatically performing this task. It was accomplished by exploiting Google's publicly available platform with a combination of 3 separate network types and post-processing techniques. Our uniquely developed NMS technique helped achieve 99.4%, valid, address specific, dwelling images.
引用
收藏
页码:473 / 480
页数:8
相关论文
共 50 条
  • [41] Google Street View Images Support the Development of Vision-Based Driver Assistance Systems
    Salmen, Jan
    Houben, Sebastian
    Schlipsing, Marc
    2012 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2012, : 891 - 895
  • [42] 'Big data' for pedestrian volume: Exploring the use of Google Street View images for pedestrian counts
    Yin, Li
    Cheng, Qimin
    Wang, Zhenxin
    Shao, Zhenfeng
    APPLIED GEOGRAPHY, 2015, 63 : 337 - 345
  • [43] Mapping the spatial distribution of shade provision of street trees in Boston using Google Street View panoramas
    Li, Xiaojiang
    Ratti, Carlo
    URBAN FORESTRY & URBAN GREENING, 2018, 31 : 109 - 119
  • [44] Measuring visual enclosure for street walkability: Using machine learning algorithms and Google Street View imagery
    Yin, Li
    Wang, Zhenxin
    APPLIED GEOGRAPHY, 2016, 76 : 147 - 153
  • [45] Using google street view panoramas to investigate the influence of urban coastal street environment on visual walkability
    Huang, Gonghu
    Yu, Yiqing
    Lyu, Mei
    Sun, Dong
    Zeng, Qian
    Bart, Dewancker
    ENVIRONMENTAL RESEARCH COMMUNICATIONS, 2023, 5 (06):
  • [46] The Promise, Practicalities, and Perils of Virtually Auditing Neighborhoods Using Google Street View
    Bader, Michael D. M.
    Mooney, Stephen J.
    Bennett, Blake
    Rundle, Andrew G.
    ANNALS OF THE AMERICAN ACADEMY OF POLITICAL AND SOCIAL SCIENCE, 2017, 669 (01): : 18 - 40
  • [47] A Novel and Simple Management System of Interactive System Using Google Street View
    Wiangsamut, Samruan
    Jareanpon, Chatklaw
    Kaewman, Sasitorn
    NEW TRENDS IN COMPUTATIONAL COLLECTIVE INTELLIGENCE, 2015, 572 : 173 - 181
  • [48] Assessing streetscape greenery with deep neural network using Google Street View
    Kameoka, Taishin
    Uchida, Atsuhiko
    Sasaki, Yu
    Ise, Takeshi
    BREEDING SCIENCE, 2022, 72 (01) : 107 - 114
  • [49] Viewing obesogenic advertising in children's neighbourhoods using Google Street View
    Egli, Victoria
    Zinn, Caryn
    Mackay, Lisa
    Donnellan, Niamh
    Villanueva, Karen
    Mavoa, Suzanne
    Exeter, Daniel J.
    Vandevijvere, Stefanie
    Smith, Melody
    GEOGRAPHICAL RESEARCH, 2019, 57 (01) : 84 - 97
  • [50] The economic value of urban landscapes in a suburban city of Tokyo, Japan: A semantic segmentation approach using Google Street View images
    Suzuki, Masatomo
    Mori, Junichiro
    Maeda, Takashi Nicholas
    Ikeda, Jun
    JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING, 2023, 22 (03) : 1110 - 1125