Vehicle tracking in wide area motion imagery from an airborne platform

Vehicle tracking in wide area motion imagery from an airborne platform

van Eekeren, A.W.M.
van Huis, J.R.
Eendebak, P.T.
Baan, J.

Rarity, J.G. (editor)
Huckridge, D.A. (editor)
Ebert, R. (editor)
Gruneisen, M.T. (editor)
Dusek, M. (editor)

2015

Airborne platforms, such as UAV's, with Wide Area Motion Imagery (WAMI) sensors can cover multiple square kilometers and produce large amounts of video data. Analyzing all data for information need purposes becomes increasingly labor-intensive for an image analyst. Furthermore, the capacity of the datalink in operational areas may be inadequate to transfer all data to the ground station. Automatic detection and tracking of people and vehicles enables to send only the most relevant footage to the ground station and assists the image analysts in effective data searches. In this paper, we propose a method for detecting and tracking vehicles in high-resolution WAMI images from a moving airborne platform. For the vehicle detection we use a cascaded set of classifiers, using an Adaboost training algorithm on Haar features. This detector works on individual images and therefore does not depend on image motion stabilization. For the vehicle tracking we use a local template matching algorithm. This approach has two advantages. In the first place, it does not depend on image motion stabilization and it counters the inaccuracy of the GPS data that is embedded in the video data. In the second place, it can find matches when the vehicle detector would miss a certain detection. This results in long tracks even when the imagery is of low frame-rate. In order to minimize false detections, we also integrate height information from a 3D reconstruction that is created from the same images. By using the locations of buildings and roads, we are able to filter out false detections and increase the performance of the tracker. In this paper we show that the vehicle tracks can also be used to detect more complex events, such as traffic jams and fast moving vehicles. This enables the image analyst to do a faster and more effective search of the data. © 2015 SPIE.

2015 Observation, Weapon & Protection Systems
II - Intelligent Imaging
TS - Technical Sciences
3D reconstruction
airborne platforms
detection
image processing
motion-in-motion
tracking
UAV
wide area motion imagery

http://resolver.tudelft.nl/uuid:a9256c9d-3e52-4de6-ada0-93fb762000f9

https://doi.org/10.1117/12.2196392

534548

SPIE

9781628418583

0277-786X

Electro-Optical and Infrared Systems: Technology and Applications XII; and Quantum Information Science and Technology, 22 September 2015 through 23 September 2015, 9648

Proceedings of SPIE - The International Society for Optical Engineering

96480I

conference paper