Wilderness search and rescue can be assisted by video searchers in manned aircraft. The video searcher's primary task is to find clues on the ground. Due to altitude, it may be difficult to resolve details on the ground with a standard video camera. As the video streams at a constant frame rate, the searcher may become distracted by other tasks. While handling these tasks the searcher may miss important clues or spend extra time flying over the search area; either outcome decreases both the effectiveness of the video searcher and the chances of successfully finding missing persons. We develop an efficient software system that allows the video searcher to deal with distractions while identifying, resolving, and geolocating clues using mixed-resolution video. We construct an inexpensive camera rig that feeds video and telemetry to this system. We also develop a simple flight simulator for generating synthetic search video for simulation and testing purposes. To validate our methods we conduct a user study and a field trial. An analysis of the user study results suggests that our system can combine the video streams without loss of performance in the primary or secondary search task. The resulting gains in screen-space efficiency can then be used to present more information, such as scene context or larger-resolution images. Additionally, the field trial suggests that the software is capable of robustly operating in a real-world environment.

Aircraft-mounted cameras have potential to greatly increase the effectiveness of wilderness search and rescue efforts by collecting photographs or video of the search area. The more data that is collected, the more difficult it becomes to process it by visual inspection alone. This work presents a method for automatically detecting unusual objects in aerial video to assist people in locating signs of missing persons in wilderness areas. The detector presented here makes use of anomaly detection methods originally designed for hyperspectral imagery. Multiple anomaly detection methods are considered, implemented, and evaluated. These anomalies are then aggregated into spatiotemporal objects by using the video's inherent spatial and temporal redundancy. The results are therefore summarized into a list of unusual objects to enhance the search technician's video review interface. In the user study reported here, unusual objects found by the detector were overlaid on the video during review. This increased participants' ability to find relevant objects in a simulated search without significantly affecting the rate of false detection. Other effects and possible ways to improve the user interface are also discussed.

Searching for lost people in a Wilderness Search and Rescue (WiSAR) scenario is a task that can benefit from large numbers of agents, some of whom may be robotic. These agents may have differing levels of autonomy, determined by the set of tasks they are performing. In addition, the level of autonomy that results in the best performance may change due to varying workload or other factors. Allowing a supervisor and a searcher to jointly decide the correct level of autonomy for a given situation (“mixed initiative”) results in better overall performance than giving an agent absolute control over their level of autonomy (“adaptive autonomy”) or giving a supervisor absolute control over the agent's level of autonomy (“adjustable autonomy”).

Mini Unmanned Aerial Vehicles (mUAVs) have the potential to be a great asset to Wilderness Search and Rescue groups by providing a bird's eye view of the search area. These vehicles can carry a variety of sensors to better understand the world below. This paper proposes using both Infrared (IR) and Visible Spectrum cameras on a mUAV for Wilderness Search and Rescue. It details a method for combining the color and heat information from these two cameras into a single fused display to reduce needed screen space for remote field use. To align the video frames for fusion, a method for simultaneously pre-calibrating the intrinsic and extrinsic parameters of the cameras and their mount using a single multi-spectral calibration rig is also presented. A user study conducted to validate the proposed image fusion methods showed no reduction in performance when detecting objects of interest in the single-screen fused display compared to a side-by-side display. Furthermore, the users' increased performance on a simultaneous auditory task showed that increased performance on a simultaneous auditory task showed that their cognitive load was reduced when using the fused display.