Wide-Area Persistent Airborne Video: Architecture and Challenges

The need for persistent video covering large geospatial areas using embedded camera networks and stand-off sensors has increased over the past decade. The availability of inexpensive, compact, light-weight, energy-efficient, high resolution optical sensors and associated digital image processing hardware has led to a new class of airborne surveillance platforms. Traditional tradeoffs posed between lens size and resolution, that is the numerical aperture of the system, can now be mitigated using an array of cameras mounted in a specific geometry. This fundamental advancement enables new imaging systems to cover very large fields of view at high resolution, albeit with spatially varying point spread functions. Airborne imaging systems capable of acquiring 88 megapixels per frame, over a wide field-of-view of 160 degrees or more at low frame rates of several hertz along with color sampling have been built using an optical array with up to eight cameras. These platforms fitted with accurate orientation sensors circle above an area of interest at constant altitude, adjusting steadily the orientation of the camera array fixed around a narrow area of interest, ideally locked to a point on the ground. The resulting image sequence maintains a persistent observation of an extended geographical area depending on the altitude of the platform and the configuration of the camera array. Suitably geo-registering and stabilizing these very large format videos provide a virtual nadir view of the region being monitored enabling a new class of urban scale activity analysis applications. The sensor geometry, processing challenges and scene interpretation complexities are highlighted. K. Palaniappan (!) University of Missouri, Columbia, MO 65211, USA e-mail: [email protected] R.M. Rao Army Research Laboratory, Adelphi, MD 20783, USA e-mail: [email protected] G. Seetharaman Air Force Research Laboratory, Rome, NY 13441, USA e-mail: [email protected] B. Bhanu et al. (eds.), Distributed Video Sensor Networks, DOI 10.1007/978-0-85729-127-1_24, © Springer-Verlag London Limited 2011 349 350 K. Palaniappan et al.