Intelligent Automation, Inc. — Department of Defense SBIR Phase II: NGA181-001

Description

Topographic features found in ground-based natural images contain information that is useful for a variety of applications including geolocation estimation and navigation. Traditionally, these features have been manually labeled by analysts which is costly and time consuming, especially considering the volume of readily available data. During Phase I, we have demonstrated a novel TOFENet framework for extracting topographic features from still images using a state-of-the-art deep learning based techniques. In this Phase II, we propose to extend the capability to video data, improve robustness to handle variations in lighting, weather and environment, and reduce false positives. IAI will build and deliver a TOFENet software ready for integration, by the end of Phase II.