Face Classification and Detection in Driving Environment

People

Dongseob Kim and Hyunjung Shim

Overview

Face Detection in driving environment is hard problem. In this work, we aim to train face detection and classification network which target to operate well on driving scenario. We first collect data of car environment, processing the data to generate database. We change conventionally used YOLO v2 network structure to fit well on our purpose. Classification IOU is average 83.59% and it can classify and detect each people's face in about 25 fps.

Detected Face Result

Average IOU : 83.59%

Average Recall : 93.14%