Long Range, Non-cooperative, Biometric Tagging, Tracking and Location

With the growing concerns surrounding security and terrorism around the world, biometrics has become one of the premier solutions to combat these problems. Traditionally, biometrics has been an academic problem that has been studied from the perspective of optimal environments (good lighting, cooperative subjects, single-frontal-2D / 3D photographs, etc.) and unlimited time and processing power. This form of biometric signature is considered"cooperative"and is generally not applicable to the more difficult problem of"real-world"recognition. Non-cooperative feature recognition is an important component to tracking as a method of distinguishing between tracking targets. Tracking and location determination can be accomplished easily on static platforms with controlled backgrounds and camera calibration, but has shown to be significantly more challenging on a mobile UAV platform. Innovative research is required to identify"non-cooperative"techniques that can be developed for implementation under modern battlefield conditions. In this proposal, we present a variety of algorithms and methods to perform tagging, tracking, and locating (TTL) imagery platforms and sensor payloads. We will leverage our prior SBIR and academic experience in this area, fusing remote biometric feature extraction with state-of-the-art image alignment, to tag, track, and locate long-range, non-cooperative targets on diverse video sensor input.