PerVision: An integrated Pervasive Computing/Computer Vision Approach to Tracking Objects in a Self-Sensing Space

We propose a novel approach to self-sensing spaces, in which classical computer vision algorithms are empowered by opportunities presented by the pervasive space. Our approach, which we call PerVision, extends classical object recognition and tracking algorithms by adding a self-assessment/adjustment loop in which sensors and actuators of the pervasive space are used to vary scene parameters to minimize errors in the recognition process. We present the PerVision concept and algorithms in the context of locating and tracking dumb objects such as furniture in a smart house. This work is a continuation of previous research in which we introduced the Smart Plug concept to locate, track, and remotely interact with appliances and electrical devices. Collectively, PerVision and Smart Plugs take us a few steps closer to realizing the ambitious vision of completely self-sensing spaces.