@inproceedings{58ba2064a7a44fd0af9383c8c96fe092,
title = "Human-AGV interaction: real-time gesture detection using deep learning",
abstract = "In this paper, we present a real-time human body gesture recognition for controlling Automated Guided Vehicle (AGV) in facility. Exploiting the breakthrough of deep convolutional networks in computers, we have developed a system that can detect the human gestures and give corresponding commands to the AGV according to different gestures. For avoiding interference of multiple operational targets in an image, we proposed a method to filter out the non-operator. In addition, we propose a human gesture interpreter with clear semantic information and build a new human gesture dataset with 8 gestures to train or fine-tune the deep neural networks for human gesture detection. In order to balance accuracy and response speed, we choose MobileNet-SSD as the detection network.",
keywords = "human gesture, AGV, mobilenet-SSD, deep learning",
author = "Jiliang Zhang and Li Peng and Wei Feng and Zhaojie Ju and Honghai Liu",
year = "2019",
month = aug,
day = "6",
doi = "10.1007/978-3-030-27541-9_20",
language = "English",
isbn = "978-3-030-27540-2",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "231--242",
editor = "Haibin Yu and Jinguo Liu and Lianquing Liu and Zhaojie Ju and Yuwang Liu and Dalin Zhou",
booktitle = "Intelligent Robotics and Applications",
note = "12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 ; Conference date: 08-08-2019 Through 11-08-2019",
}