Establishing a common coordinate view in multiple moving aerial cameras

Abstract

A camera mounted on an aerial vehicle provides an excellent means of monitoring large areas of a scene. Utilizing several such cameras on different aerial vehicles allows further flexibility, in terms of increased visual scope and in the pursuit of multiple targets. The underlying concept of such co-operative sensing is to use inter-camera relationships to give global context to 'locally' obtained information at each camera. It is desirable, therefore, that the data collected at each camera and the inter-camera relationship discerned by the system be presented in a coherent visualization. Since the cameras are mounted on UAVs, large swaths of areas may be traversed in a short period of time, coherent visualization is indispensable for applications like surveillance and reconnaissance. While most visualization approaches have hitherto focused on data from a single camera at a time, as a consequence of tracking objects across cameras, we show that widely separated mosaics can be aligned, both in space and color, for concurrent visualization. Results are shown on a number of real sequences, validating our qualitative models.