Vehicle tracking under occlusion conditions using directional ringlet intensity feature transform

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.