Skip to main content
SpringerLink
Log in

A Web-Based Visualization Tool for 3D Spatial Coverage Measurement of Aerial Images

  • Conference paper
  • First Online:
MultiMedia Modeling (MMM 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11962))

Included in the following conference series:

Abstract

Drones are becoming popular in different domains, from personal to professional usages. Drones are usually equipped with high-resolution cameras in addition to various sensors (e.g., GPS, accelerometers, and gyroscopes). Therefore, aerial images captured by drones are associated with spatial metadata that describe the spatial extent per image, referred to as aerial field-of-view (Aerial FOV). Aerial FOVs can be utilized to represent the visual coverage of a particular region with respect to various viewing directions at fine granular-levels (i.e., small cells composing the region). In this demo paper, we introduce a web tool for interactive visualization of a collection of aerial field-of-views and instant measurement of their spatial coverage over a given 3D space. This tool is useful for several real-world monitoring applications that are based on aerial images to simulate the 3D spatial coverage of the collected visual data in order to analyze their adequacy.

A. Alfarrarjeh, Z. Ma—These authors contributed equally to this work.

Z. Ma—This author contributed to this work during his research visit at USC.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    The success of smart city applications based on ground images (e.g., street cleanliness classification [1] and material recognition [3]) encouraged utilizing drone images for other applications.

  2. 2.

    In the existing FOVs, yaw angles (\({\theta }_{y}\)) varies widely.

  3. 3.

    WebGL is an extended version of OpenGL (a standard library in computer graphics) for web content rendered in a web browser.

References

  1. Alfarrarjeh, A., et al.: Image classification to determine the level of street cleanliness: a case study. In: BigMM, pp. 1–5. IEEE (2018)

    Google Scholar 

  2. Alfarrarjeh, A., et al.: Spatial coverage measurement of geo-tagged visual data: a database approach. In: BigMM, pp. 1–8. IEEE (2018)

    Google Scholar 

  3. Alfarrarjeh, A., et al.: Recognizing material of a covered object: a case study with graffiti. In: ICIP, pp. 2491–2495. IEEE (2019)

    Google Scholar 

  4. Alfarrarjeh, A., et al.: A Web-Based Visualization Tool for 3D spatial coverage measurement of aerial images. In: Cheng, W.-H., et al. (eds.) MMM 2020. LNCS, vol. 11962, pp. 715–721. Springer, Cham (2020)

    Google Scholar 

  5. Alfarrarjeh, A., et al.: Scalable spatial crowdsourcing: a study of distributed algorithms. In: MDM, vol. 1, pp. 134–144. IEEE (2015)

    Google Scholar 

  6. Del, B.A., et al.: Visual coverage using autonomous mobile robots for search and rescue applications. In: SSRR, pp. 1–8. IEEE (2013)

    Google Scholar 

  7. Kazemi, L., Shahabi, C.: Geocrowd: enabling query answering with spatial crowdsourcing. In: SIGSPATIAL GIS, pp. 189–198. ACM (2012)

    Google Scholar 

  8. Kim, S.H., et al.: TVDP: Translational visual data platform for smart cities. In: ICDEW, pp. 45–52. IEEE (2019)

    Google Scholar 

  9. Lu, Y., Shahabi, C.: Efficient indexing and querying of geo-tagged aerial videos. In: SIGSPATIAL GIS, pp. 1–10. ACM (2017)

    Google Scholar 

  10. Oettershagen, P., et al.: Long-endurance sensing and mapping using a hand-launchable solar-powered UAV. In: Wettergreen, D.S., Barfoot, T.D. (eds.) Field and Service Robotics. STAR, vol. 113, pp. 441–454. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-27702-8_29

    Chapter  Google Scholar 

  11. Oettershagen, P., et al.: Design of small hand-launched solar-powered UAVs: from concept study to a multi-day world endurance record flight. J. Field Robot. 34(7), 1352–1377 (2017)

    Article  Google Scholar 

  12. Papatheodorou, S., et al.: Collaborative visual area coverage. Robot. Auton. Syst. 92, 126–138 (2017)

    Article  Google Scholar 

Download references

Acknowledgment

This work was supported in part by NSF grants IIS-1320149 and CNS-1461963, the USC Integrated Media Systems Center, and unrestricted cash gifts from Oracle and Google.

Author information

Authors and Affiliations

  1. Integrated Media Systems Center, University of Southern California, Los Angeles, USA

    Abdullah Alfarrarjeh, Seon Ho Kim, Yeonsoo Park & Cyrus Shahabi

  2. Electronic Engineering Department, Tsinghua University, Beijing, China

    Zeyu Ma

Authors
  1. Abdullah Alfarrarjeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zeyu Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Seon Ho Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yeonsoo Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cyrus Shahabi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abdullah Alfarrarjeh .

Editor information

Editors and Affiliations

  1. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Yong Man Ro

  2. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Huang Cheng

  3. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Junmo Kim

  4. National Cheng Kung University, Tainan City, Taiwan

    Wei-Ta Chu

  5. Tsinghua University, Beijing, China

    Peng Cui

  6. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Jung-Woo Choi

  7. National Tsing Hua University, Hsinchu, Taiwan

    Min-Chun Hu

  8. Ghent University, Ghent, Belgium

    Wesley De Neve

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Alfarrarjeh, A., Ma, Z., Kim, S.H., Park, Y., Shahabi, C. (2020). A Web-Based Visualization Tool for 3D Spatial Coverage Measurement of Aerial Images. In: Ro, Y., et al. MultiMedia Modeling. MMM 2020. Lecture Notes in Computer Science(), vol 11962. Springer, Cham. https://doi.org/10.1007/978-3-030-37734-2_59

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-37734-2_59

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37733-5

  • Online ISBN: 978-3-030-37734-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation