“Open Vision Platform for Smart City Intersections & VQA from Camera Networks” is a one-year capstone project as part of the Master of Science in Computer Vission (MSCV) program offered by the Robotics Institute, Carnegie Mellon University and is sponsored by the Zensors. Inc, a spin-off company from CMU focused on turning cameras into smart IoT sensors for actionable business insights. The capstone project has multiple sections that targeting at different research problems in the broad field of computer vision.
Open Vision Platform for Smart City Intersections
In modern cities, streets are bustling with lots of vehicles, pedestrains and other activities, which sometimes can be dangerous. When multiple vehicles from different directions trying to occupy the same place, accidents could happen easily.
To enable smart city innovation, the smart intersection is essential and important.
To prevent fatal accidents from happening, we are using computer vision and machine learning techniques to analyze and understand the behaviors of various road users. We are developing algorithms to detect vehicles and pedestrains, to track their trajectories and to predict their future behaviors with CCTV live camera.
VQA from Camera Networks
Zensors, spun-off of Carnegie Mellon University, wants to enable smart and reactive spaces through cutting-edge computer vision technologies. We are working with Zensors to develop state-of-the-art machine learning algorithms to help their customers to address their concerns. They are ranging from counting people and cars, to more complex questions, such as table cleanliness and equipment utilizations.