Camera-equipped mini-UAVs are popular for many applications, including search and surveillance, but video
from them is commonly plagued with distracting jittery motions and disorienting rotations that make it difficult for human viewers to detect objects of interest and infer spatial relationships. For time-critical search situations there are also inherent tradeoffs between detection and search speed. These problems make the use of dynamic mosaics to expand the spatiotemporal properties of the video appealing. However, for many applications it may not be necessary to maintain full mosaics of all of the video but to mosaic and retain only a number of recent (temporally local) frames, still providing a larger field of view and effectively longer temporal view as well as natural stabilization and consistent orientation. This paper presents and evaluates a real-time system for displaying live video to human observers in search situations by using temporally local mosaics while avoiding masking effects from dropped or noisy frames. Its primary contribution is an empirical study of the effectiveness of using such methods for enhancing human detection of objects of interest, which shows that temporally local mosaics increase task performance and are easier for humans to use than non-mosaiced methods, including stabilized video.