Digital Assistance for Quality Assurance: Augmenting Workspaces Using Deep Learning for Tracking

Digital Assistance for Quality Assurance: Augmenting Workspaces Using Deep Learning for Tracking NearSymmetrical Objects João Belo, Andreas Fender, Tiare Feuchtner, Kaj Grønbæk ISS 19: ACM International Conference on Interactive Surfaces and Spaces Session: Physical Spaces Interactions Abstract We present a digital assistance approach for applied metrology on nearsymmetrical objects. In manufacturing, systematically measuring products for quality assurance is often a manual task, where the primary ch