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Vehicle Tracking under Occlusion Conditions using Directional Ringlet Intensity Feature Transform
2015 National Aerospace and Electronics Conference
Document Type
Conference Paper
Publication Date
6-1-2015
Abstract
The tracking of vehicles in wide area motion imagery (WAMI) can be a challenge due to the full and partial occlusions that can occur. The proposed solution for this challenge is to use the Directional Ringlet Intensity Feature Transform (DRIFT) feature extraction method with a Kalman filter. The proposed solution will utilize the properties of the DRIFT feature to solve the partial occlusion challenges. The Kalman filter will be used to estimate the object location during a full occlusion. The proposed solution will be tested on several vehicle sequences from the Columbus Large Image Format (CLIF) dataset.
ISBN/ISSN
2379-2027
Copyright
Copyright © 2015, IEEE
Publisher
IEEE
Place of Publication
Dayton, OH
Disciplines
Citation Information
Evan Krieger, Paheding Sidike, Theus H. Aspiras and Vijayan K. Asari. "Vehicle Tracking under Occlusion Conditions using Directional Ringlet Intensity Feature Transform" 2015 National Aerospace and Electronics Conference (2015) Available at: http://works.bepress.com/vijayan_asari/27/
Permission documentation is on file.