Abstract
Accurate and efficient object tracking is an important aspect of various security and surveillance applications. In object tracking solutions which utilize intensity-based histogram feature methods for use on wide area motion imagery (WAMI), there currently exists tracking challenges due to object structural information distortions and pavement/background variations. The inclusion of structural target information including edge features in addition to the intensity features will allow for more robust object tracking. To achieve this we propose a feature extraction method that utilizes the Frei-Chen edge detector and Gaussian ringlet feature mapping. Frei-Chen edge detector extracts edge, line, and mean features that can be used to represent the structural features of the target. Gaussian ringlet feature mapping is used to obtain rotational invariant features that are robust to target and viewpoint rotation. These aspects are combined to create an efficient and robust tracking scheme. The proposed scheme is evaluated against state-of-the-art feature tracking methods using both temporal and spatial robustness metrics. The evaluations yield more accurate results for the proposed method on challenging WAMI sequences.