Security Enhancement using Machine Learning for Concealed Object Detection

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This EngagePlus is a continuation of the research project started in Engage Grant, involving the BiometricTechnologies Laboratory (BTLab) at the University of Calgary and Patriot One Technologies Inc. (PatriotOne).The project is related to enhancing security in public places by developing systems for illicit concealed objectsdetection. The BTLab researchers applied soft biometrics such as gait and body action, collected usingRGB-depth sensors, to assist PatriotOne is developing their object detection using an ultra-wide band cognitiveradar.The two main objectives of the proposed Engage Plus Grant are as follows:(1) Fully integrate the developed algorithms and the depth data collected using RGB-depth sensors with thePartriotOne experimental data collection protocol.(2) Continue research and development on Generative Adversarial Networks for helping reduce thecumbersome task of data collection for training the PatrioOne system.Ultimately, the collaboration between BTLab and PatriotOne during the Engage Plus will result in the researchand development of a novel process to design and test radar systems for concelaed object detection in real-time.The novel design process will assist PatriotOne in improving their system to bring to a finalized commercialproduct.