Description

People detection and tracking using yolo v3 -open cv -deep learning

In this project, presents a technical approach related to the video computer analysis, to detect people and track the people using yolo v3 algorithm. To detect the people in public place can be a benefit for understanding the share of overall traffic your area is attracting. Find out what, encourage We use surveillance cameras, which located in the museum. We offered two methods, the first method for detecting people in a closed space and second method finding density areas which people more spend time to visit. The YOLO model makes predictions with a single network evaluation. Systems like R-CNN and Faster R-CNN, make multiple assessments for a single image, making YOLO extremely fast, running in real-time with a capable GPU. For detect people used YOLOv3 algorithm which is published by and shows that it has high accuracy to identify people. And for finding density areas, We utilized a background subtraction with Gaussian Mixture algorithms and heatmap colour technique to analysis each frame and figure out, where are the density areas which shows people like to spend more time to visit.