Small Object Detection Base on YOLOv3 for Pedestrian Recognition

In this work we will detect pedestrians on road using Deep Learning Techniques. Both detection and tracking people are challenging problems, especially in complex real-world scenes that commonly involve multiple people, complicated occlusions, and cluttered or even moving backgrounds. People detectors have been shown to be able to locate pedestrians even in complex street scenes, but false positives have remained frequent. 

The identification of particular individuals has remained challenging as well. The approximate articulation of each person is detected using YOLOv2 pretrained detector network. The Dataset used here is collected from Kaggle pedestrian’s dataset.

 Keywords: Detection, Convolution Neural network, Deep Learning, YOLOV2.