Range sensing and environmental simulation for smart lighting applications

Abstract

Next, we extend the time-of-flight occupancy sensing framework to the new Smart Conference Room constructed on the Rensselaer Polytechnic Institute (RPI) campus, using a ceiling-mounted array of time-of-flight cameras. This large environment brings new challenges and requires new algorithm modifications. We discuss the challenges and propose corresponding solutions, including multi-sensor interference elimination, integration of sensors in the development environment of a smart lighting system, and calibration of height measurements for robust pose estimation. We also improve the tracking algorithm by using the location, height, area and shape information for blob matching. This up-scaled tracking system is validated with experiments on full-scale time-of-flight videos recorded in the conference room with multiple occupants walking around.