Helpdesk

Top image

Editorial board

Juraj Altus
University of Zilina, Slovakia

Alexander Argyros
The University of Sydney, Australia

Radu Arsinte
Technical University of Cluj Napoca, Romania

Ivan Baronak
Slovak University of Technology, Slovakia

Dalibor Biolek
University of Defence, Czech Republic

Klara Capova
University of Zilina, Slovakia

Ray-Guang Cheng
National Taiwan University of Science and Technology, Taiwan, Province of China

Erik Chromy
Slovak University of Technology, Slovakia

Frantisek Cvachovec
University of Defence, Czech Republic

Annraoi M de Paor
University College Dublin, Ireland

Milan Dado
University of Zilina, Slovakia

Zdenek Divis
VSB - Technical University of Ostrava, Czech Republic

Petr Drexler
Brno University of Technology, Czech Republic

Pavel Fiala
Brno University of Technology, Czech Republic

Maria Franekova
University of Zilina, Slovakia

Eva Gescheidtova
Brno University of Technology, Czech Republic

Valeria Hrabovcova
University of Zilina, Slovakia

Gokhan Hakki Ilk
Ankara University, Turkey

Rene Kalus
VSB - Technical University of Ostrava, Czech Republic

Ivan Kasik
Academy of Sciences of the Czech Republic, Czech Republic

Vladimir Kasik
VSB - Technical University of Ostrava, Czech Republic

Matej Kavacky
Slovak University of Technology, Slovakia

Jan Kohout
University of Defence, Czech Republic

Pavel Koktavy
Brno University of Technology, Czech Republic

Ondrej Krejcar
University of Hradec Kralove, Czech Republic

Igor Piotr Kurytnik
University of Bielsko-Biala, Poland

Miroslaw Luft
Technical University of Radom, Poland

Stanislav Marchevsky
Technical University of Kosice, Slovakia

Radek Martinek
VSB - Technical University of Ostrava, Czech Republic

Luigi Martirano
University of Rome "La Sapienza", Italy

Jerzy Mikulski
University of Economics in Katowice, Katowice, Poland

Karol Molnar
Honeywell International, Czech Republic

Miloslav Ohlidal
Brno University of Technology, Czech Republic

Ibrahim Taner Okumus
Sutcu Imam University, Turkey

Milos Orgon
Slovak University of Technology, Slovakia

Marek Penhaker
VSB - Technical University of Ostrava, Czech Republic

Wasiu Oyewole Popoola
The University of Edinburgh, United Kingdom

Roman Prokop
Tomas Bata University in Zlin, Czech Republic

Karol Rastocny
University of Zilina, Slovakia

Marie Richterova
University of Defence, Czech Republic

Gheorghe Sebestyen-Pal
Technical University of Cluj Napoca, Romania

Sergey Vladimirovich Serebriannikov
National Research University "MPEI", Russian Federation

Yuriy Shmaliy
Guanajuato University, Mexico

Vladimir Schejbal
University of Pardubice, Czech Republic

Bohumil Skala
University of West Bohemia in Plzen, Czech Republic

Lorand Szabo
Technical University of Cluj Napoca, Romania

Adam Szelag
Warsaw University of Technology, Poland

Ahmadreza Tabesh
Isfahan University of Technology, Iran, Islamic Republic Of

Pavel Vaclavek
Brno University of Technology, Czech Republic

Martin Vaculik
University of Zilina, Slovakia

Viktor Valouch
Academy of Sciences of the Czech Republic, Czech Republic

Vladimir Vasinek
VSB - Technical University of Ostrava, Czech Republic

Jiri Vodrazka
Czech Technical University in Prague, Czech Republic

Miroslav Voznak
VSB - Technical University of Ostrava, Czech Republic

Otakar Wilfert
Brno University of Technology, Czech Republic

Jan Zidek
VSB - Technical University of Ostrava, Czech Republic


Home Search Mail RSS


Human Detection System by Fusing Depth Map-Based Method and Convolutional Neural Network-Based Method

Anh Vu Le, Tran Tin Phu, Jong Suk Choi, Jan Skapa, Miroslav Voznak

DOI: 10.15598/aeee.v15i4.2377


Abstract

In this paper, the depth images and the colour images provided by Kinect sensors are used to enhance the accuracy of human detection. The depth-based human detection method is fast but less accurate. On the other hand, the faster region convolutional neural network-based human detection method is accurate but requires a rather complex hardware configuration. To simultaneously leverage the advantages and relieve the drawbacks of each method, one master and one client system is proposed. The final goal is to make a novel Robot Operation System (ROS)-based Perception Sensor Network (PSN) system, which is more accurate and ready for the real time application. The experimental results demonstrate the outperforming of the proposed method compared with other conventional methods in the challenging scenarios.

Keywords


Human detection, deep learning, fusion, ROS.

Full Text:

PDF