Full Content is available to subscribers

Subscribe/Learn More  >
Proceedings Article

Tracking small targets in wide area motion imagery data

[+] Author Affiliations
Alex Mathew, Vijayan K. Asari

Univ. of Dayton (United States)

Proc. SPIE 8663, Video Surveillance and Transportation Imaging Applications, 86630A (March 19, 2013); doi:10.1117/12.2002880
Text Size: A A A
From Conference Volume 8663

  • Video Surveillance and Transportation Imaging Applications
  • Robert Paul Loce; Eli Saber; Sreenath Rao Vantaram
  • Burlingame, California, USA | February 03, 2013

abstract

Object tracking in aerial imagery is of immense interest to the wide area surveillance community. In this paper, we propose a method to track very small targets such as pedestrians in AFRL Columbus Large Image Format (CLIF) Wide Area Motion Imagery (WAMI) data. Extremely small target sizes, combined with low frame rates and significant view changes, make tracking a very challenging task in WAMI data. Two problems should be tackled for object tracking frame registration and feature extraction. We employ SURF for frame registration. Although there are several feature extraction methods that work reasonably well when the scene is of high resolution, most methods fail when the resolution is very low. In our approach, we represent the target as a collection of intensity histograms and use a robust statistical distance to distinguish between the target and the background. We divide the object into m ×n regions and compute the normalized intensity histogram in each region to build a histogram matrix. The features can be compared using the histogram comparison techniques. For tracking, we use a combination of a bearing-only Kalman filter and the proposed feature extraction technique. The problem of template drift is solved by further localizing the target with a blob detection algorithm. The new template is taken as the detected blob. We show the robustness of the algorithm by giving a comparison of feature extraction part of our method with other feature extraction methods like SURF, SIFT and HoG and tracking part with mean-shift tracking. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Alex Mathew and Vijayan K. Asari
" Tracking small targets in wide area motion imagery data ", Proc. SPIE 8663, Video Surveillance and Transportation Imaging Applications, 86630A (March 19, 2013); doi:10.1117/12.2002880; http://dx.doi.org/10.1117/12.2002880


Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).

Figures

Tables

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.