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Aerial videos taken by a drone not too far above the surface may contain thedrone's shadow projected on the scene. This deteriorates the aesthetic qualityof videos. With the presence of other shadows, shadow removal cannot bedirectly applied, and the shadow of the drone must be tracked. Tracking adrone's shadow in a video is, however, challenging. The varying size, shape,change of orientation and drone altitude pose difficulties. The shadow can alsoeasily disappear over dark areas. However, a shadow has specific propertiesthat can be leveraged, besides its geometric shape. In this paper, weincorporate knowledge of the shadow's physical properties, in the form ofshadow detection masks, into a correlation-based tracking algorithm. We capturea test set of aerial videos taken with different settings and compare ourresults to those of a state-of-the-art tracking algorithm.

Drone Shadow Tracking