A benchmark for vehicle detection on wide area motion imagery

Joseph Catrambone; Ismail Amzovski; Pengpeng Liang; Erik Blasch; Carolyn Sheaff; Zhonghai Wang; Genshe Chen; Haibin Ling

doi:10.1117/12.2178535

22 May 2015 A benchmark for vehicle detection on wide area motion imagery

Joseph Catrambone, Ismail Amzovski, Pengpeng Liang, Erik Blasch, Carolyn Sheaff, Zhonghai Wang, Genshe Chen, Haibin Ling

Author Affiliations +

Proceedings Volume 9469, Sensors and Systems for Space Applications VIII; 94690F (2015) https://doi.org/10.1117/12.2178535
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

Wide area motion imagery (WAMI) has been attracting an increased amount of research attention due to its large spatial and temporal coverage. An important application includes moving target analysis, where vehicle detection is often one of the first steps before advanced activity analysis. While there exist many vehicle detection algorithms, a thorough evaluation of them on WAMI data still remains a challenge mainly due to the lack of an appropriate benchmark data set. In this paper, we address a research need by presenting a new benchmark for wide area motion imagery vehicle detection data. The WAMI benchmark is based on the recently available Wright-Patterson Air Force Base (WPAFB09) dataset and the Temple Resolved Uncertainty Target History (TRUTH) associated target annotation. Trajectory annotations were provided in the original release of the WPAFB09 dataset, but detailed vehicle annotations were not available with the dataset. In addition, annotations of static vehicles, e.g., in parking lots, are also not identified in the original release. Addressing these issues, we re-annotated the whole dataset with detailed information for each vehicle, including not only a target’s location, but also its pose and size. The annotated WAMI data set should be useful to community for a common benchmark to compare WAMI detection, tracking, and identification methods.

Citation Download Citation

Joseph Catrambone, Ismail Amzovski, Pengpeng Liang, Erik Blasch, Carolyn Sheaff, Zhonghai Wang, Genshe Chen, and Haibin Ling "A benchmark for vehicle detection on wide area motion imagery", Proc. SPIE 9469, Sensors and Systems for Space Applications VIII, 94690F (22 May 2015); https://doi.org/10.1117/12.2178535

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available