Person searching through an omnidirectional camera using CNN in the tsukuba challenge

Shingo Nakamura, Tadahiro Hasegawa, Tsubasa Hiraoka, Yoshinori Ochiai, Shin’Ichi Yuta

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The Tsukuba Challenge is a competition, in which autonomous mobile robots run on a route set on a public road under a real environment. Their task includes not only simple running but also finding multiple specific persons at the same time. This study proposes a method that would realize person searching. While many person-searching algorithms use a laser sensor and a camera in combination, our method only uses an omnidirectional camera. The search target is detected using a convolutional neural network (CNN) that performs a classification of the search target. Training a CNN requires a great amount of data for which pseudo images created by composition are used. Our method is implemented in an autonomous mobile robot, and its performance has been verified in the Tsukuba Challenge 2017.

Original languageEnglish
Pages (from-to)540-551
Number of pages12
JournalJournal of Robotics and Mechatronics
Volume30
Issue number4
DOIs
Publication statusPublished - 2018 Aug

Keywords

  • Convolutional neural networks
  • Omnidirectional camera
  • Person searching
  • Tsukuba challenge

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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