Blind swimmer detection and notification utilizing OpenCV on the Android platform

Abstract: For a blind swimmer to be able to exercise in a swimming pool today, human assistance is required to notifying the swimmer in due time when and if she is too close to the edge. The purpose of this thesis was to see whether or not it is possible to replace and even improve the human intervention using a warning system built around a tablet mounted next to the pool edge. A secondary goal was to evaluate how suitable a tablet pc is for robotic applications. The system proposed utilizes a tablet’s built-in frontal facing camera, OpenCV as vision library, FM modules for the wireless warning system and is intended for the Android environment. Videos of the real scenario have been analyzed on a computer using OpenCV and a detection algorithm searching for the swimmer’s red swimming cap has been developed. Next, the algorithm was implemented on an Android tablet. The result obtained shows that it is perfectly possible to use a cheap tablet to accurately detect and notify the blind swimmer in due time when she is too close to the edge. If calibrated thoroughly, the likelihood of a missed detection is actually lower with this system as compared to human intervention, as humans can only warn the swimmer when she is above the water.