Capacity of pervasive camera based communication under perspective distortions

Abstract

Cameras are ubiquitous and increasingly being used not just for capturing images but also for communicating information. For example, the pervasive QR codes can be viewed as communicating a short code to camera-equipped sensors and recent research has explored using screen-to-camera communications for larger data transfers. Such communications could be particularly attractive in pervasive camera based applications, where such camera communications can reuse the existing camera hardware and also leverage from the large pixel array structure for high data-rate communication. While several prototypes have been constructed, the fundamental capacity limits of this novel communication channel in all but the simplest scenarios remains unknown. The visual medium differs from RF in that the information capacity of this channel largely depends on the perspective distortions while multipath becomes negligible. In this paper, we create a model of this communication system to allow predicting the capacity based on receiver perspective (distance and angle to the transmitter). We calibrate and validate this model through lab experiments wherein information is transmitted from a screen and received with a tablet camera. Our capacity estimates indicate that tens of Mbps is possible using a smartphone camera even when the short code on the screen images onto only 15% of the camera frame. Our estimates also indicate that there is room for at least 2.5x improvement in throughput of existing screen - camera communication prototypes.