Motion Detection and Object Detection: Yolo (You Only Look Once)
The YOLOv3 (Version 3) model makes predictions with a single network evaluation, making this method extremely fast, running in real time with a capable GPU, and this implementation is going to use a simply webcam and Y OLO algorithm.
Abstract
Recently, the field of artificial intelligence has seen many advances thanks to deep learning and image processing. It is now possible to recognize images or even find objects inside an image with a standard GPU. Image processing is a recent science that aims to provide specialists from different areas, as to the general public, tools for manipulating these digital data from the real world. The detection of moving objects is a crucial step for systems based on image processing. The movements detected by the classic algorithms are not necessarily interesting for a thorough information search, and the need to distinguish the coherent movements of parasitic movements exists in most cases. In this paper we are going to use a simply webcam and YOLO algorithm for this implementation. The YOLOv3 (Version 3) model makes predictions with a single network evaluation, making this method extremely fast, running in real time with a capable GPU. From there we'll use OpenCV, Python, and deep learning to apply the YOLOv3 object to images and apply YOLOv3 to video streams.