Implementation of an Indoor Optical Camera Communication and Localization Fusion System Using Infrared LED Markers

Recently, with the development of communication and positioning technologies, progressively higher demands have been placed on the timeliness of indoor communication and the effectiveness of indoor positioning. This paper proposes a low-cost and full-time domain coverage indoor communication and localization fusion system that uses an infrared camera to identify mobile LEDs based on region of interest optical camera communication (RoI-OCC) and calculate three-dimensional (3D) world coordinates based on perspective-n-point (PnP) algorithm. An intermediate delimiter modulation-demodulation method is designed to achieve asynchronous OCC. In processing infrared images, a region-growth-based absolute-directional-mean-difference (RG-ADMD) algorithm is developed to detect infrared targets and recover the scale. Additionally, a local-contrast-method-based Lucas-Kanade (LCM-LK) optical flow estimation algorithm is designed to track infrared targets and determine the centroid coordinates of pixels. In a 5×5 m experimental area, the established system can achieve a target detection recall rate of over 85%, the asynchronous OCC with error-free transmission and an average 3D positioning accuracy of 2.01 cm under a LCM-LK tracking algorithm.