AI-Enhanced Camouflaged Movement Detection (CMD) in Battlefield

Camouflaged movement detection in battlefield is a challenge and has not been resolved by the current technology. With the rapid development of deep learning /artificial intelligence, this challenge can be tackled. The Phase-I effort proposed by Spectral Energies LLC (SE) and Wright State University (WSU) is to demonstrate and build an integrated AI-enhanced Imaging System for the detection of camouflaged movement in the critical battlefield. The concept is to utilize the well-trained deep learning model combined with optical flow method for small movement detection to aid in the automatic detection of camouflaged movement of people or weapons with cameras on air drones under critical complex battlefield environment.  This imaging system will be designed, constructed, and tested in the laboratory, and then tested in a large-scale real-life simulated battlefield. The proposed imaging system can significantly increase the vision capability of Air Force and army in the critical battlefield environment. The final developed commercial product can be equipped into Air Force for camouflaged target detection.