Capturing aerial imagery at high resolutions often leads to very low frame rate video streams, well under full motion video standards, due to bandwidth, storage, and cost constraints. Low frame rates make registration difficult when an aircraft is moving at high speeds or when global positioning system (GPS) contains large errors or it fails. We present a method that takes advantage of persistent cyclic video data collections to perform an online registration with drift correction. We split the persistent aerial imagery collection into individual cycles of the scene, identify and correct the registration errors on the first cycle in a batch operation, and then use the corrected base cycle as a reference pass to register and correct subsequent passes online. A set of multi-view panoramic mosaics is then constructed for each aerial pass for representation, presentation and exploitation of the 3D dynamic scene. These sets of mosaics are all in alignment to the reference cycle allowing their direct use in change detection, tracking, and 3D reconstruction/visualization algorithms. Stereo viewing with adaptive baselines and varying view angles is realized by choosing a pair of mosaics from a set of multi-view mosaics. Further, the mosaics for the second pass and later can be generated and visualized online as their is no further batch error correction.

In this paper we propose a fast method for constructing multi-view stereo panoramas using a layering approach. Constructing panoramas requires accurate camera pose estimation and will often require an image blending or interpolation method to generate seamless results. We use a registration error correction method that provides globally corrected and fast results for paths that create cycles such as circular paths, back and forth straight sweeps, and even a single sweep. Then we apply our layering approach to generate multi-view stereo panoramas quickly for time sensitive applications that require immediate results and 3D perception.

Recent improvements in laser vibrometry and day/night infrared (IR) and electro-optical (EO) imaging technology have created the opportunity to create a long-range multimodal surveillance system. This multimodal capability would greatly improve security force performance through clandestine listening of targets that are probing or penetrating a perimeter defense. This system could also provide the feeds for advanced face and voice recognition systems.