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Vehicle tracking through the exploitation of remote sensing and LWIR polarization science

Vehicle tracking is an integral component in layered sensing exploitation applications. The utilization of a combination of sensing modalities and processing techniques provides better insight about a situation than can be achieved with a single sensing modality. In this work, several robust features are explored for vehicle tracking using data captured in a remote sensing setting. A target area is surveyed by a sensor operating capturing polarization information in the longwave infrared (LWIR) band. We here extend our previous work ([1]) to experimental analysis of several feature sets including three classic features (Stokes images, DoLP, the Degree of Linear Polarization, and AoP, the Angle of Polarization) and several geometry inspired features.1