Recently, commercial Small Unmanned Aerial Systems (sUAS) have become very popular for real-time inspection tasks due to their cost-effectiveness at covering large areas quickly. Within these tasks, many objects of interest are best characterized by their 3D geometry. This is particularly true when considering the false alarm rates associated with automated analysis of features with irregular appearance, but well-characterized geometry. However, sUAS and low-cost sensors present challenges for sUAS tasks due to the limitations in payload and sensor quality. We examine the effectiveness of multi-view stereo and commercial LIDAR in the domain of rapid airfield damage assessment. On-board cameras that can capture high-resolution video and still images are ubiquitous in the commercial sUAS market. Multi-view stereo provides an approach that extracts dense 3D points for a scene, creating an appealing solution that requires no additional hardware for most sUAS. Recent advances in multi-view stereo approach real-time processing rates, and provide excellent stability. Also, commercial LIDAR prices have dropped dramatically in recent years, along with the size, weight, and power (SWaP) of these devices. However, typical applications of airborne LIDAR require a highly tuned motion measurement suite. We examine the processing and performance trade-offs associated with each of these approaches in the context of rapid airfield damage assessment. We examine flight time, minimum object size, processing time, SWaP, and detection and false alarm rates over a test area of approximately 35,000 square meters.
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