Falls represent one of the most severe issues faced by the elder population. Therefore,in this work, we propose a system for fall detection using RGB camera images. In thisregard, we propose, associated to multiple classifiers, a fusion between features calculatedfrom the head region and those calculated from the whole body’s region. These regionsare extracted using the YOLOv5 object detector. Experiments conducted on a standardfall dataset showed satisfying and promising results. The system based on features fromthe head data yielded an accuracy of 94.79%, while the system based on fusion betweenhead and body features produced an accuracy of 98.08%.