Journal of Robotics, Networking and Artificial Life

Volume 7, Issue 2, September 2020, Pages 137 - 141

Detecting Pedestrians and Their Walk Directions Using a MY VISION System

Authors
Joo Kooi Tan1, *, Kenta Hori2, Seiji Ishikawa3
1Faculty of Engineering, Kyushu Institute of Technology, Kitakyushu, Fukuoka 804-8550, Japan
2Graduate School of Engineering, Kyushu Institute of Technology, Kitakyushu, Fukuoka 804-8550, Japan
3Kyushu Institute of Technology
*Corresponding author. Email: etheltan@cntl.kyutech.ac.jp
Corresponding Author
Joo Kooi Tan
Received 10 November 2019, Accepted 18 May 2020, Available Online 4 June 2020.
DOI
10.2991/jrnal.k.200528.014How to use a DOI?
Keywords
MY VISION; ego-cameras; optical flow; MSC-HOG; HOF; pedestrian detection; walk direction
Abstract

This paper proposes a pedestrian detection method using a MY VISION system. The MY VISION system is an image processing system using an ego-camera which a user of the system possesses, and it is expected to be the third eye of those who are aged, visually impaired or even those who are absorbed in a mobile-phone while walking. In the proposed method, a flow area different from camera movement is extracted first on the image provided from a user’s head-mounted camera. The area is a candidate area where pedestrians may exist. Multiple scale cell-histograms of oriented gradients features are then calculated to detect pedestrians in the area. Histograms of optical flow feature is further computed to recognize the moving direction of the detected pedestrians. The proposed method was examined its performance experimentally and satisfactory results were obtained.

Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)
View full text (HTML)

Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
7 - 2
Pages
137 - 141
Publication Date
2020/06/04
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
10.2991/jrnal.k.200528.014How to use a DOI?
Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Joo Kooi Tan
AU  - Kenta Hori
AU  - Seiji Ishikawa
PY  - 2020
DA  - 2020/06/04
TI  - Detecting Pedestrians and Their Walk Directions Using a MY VISION System
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 137
EP  - 141
VL  - 7
IS  - 2
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.k.200528.014
DO  - 10.2991/jrnal.k.200528.014
ID  - Tan2020
ER  -