Car tracking in rear view based on bicycle specific motions in vertical vibration and angular variation via prediction and likelihood models with particle filter for rear confirmation support

Norikazu Ikoma, Yohei Mikami, Takeshi Ikenaga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Aiming at rear confirmation support of a bicycle, our objective is to track of a car in rear view captured by a camera settled under the saddle. Where specific motions of bicycle such as angular variation and vertical vibration are necessary to cope with. We propose a novel state space model coping with the two specific motions and utilize particle filter for state estimation. For angular variation, an elaborated system noise with variable mean having larger pulling force for larger angle. For likelihood model to cope with vertical vibration, we propose an elaborated likelihood evaluation having more sensitive feature for horizontal while less sensitive for vertical motion. Experimental result with real scene videos achieves 74.24 percent precision of the tracking.

Original languageEnglish
Title of host publicationWorld Automation Congress Proceedings
PublisherIEEE Computer Society
Pages279-284
Number of pages6
ISBN (Electronic)9781889335490
DOIs
Publication statusPublished - 2014 Oct 24
Event2014 World Automation Congress, WAC 2014 - Waikoloa, United States
Duration: 2014 Aug 32014 Aug 7

Publication series

NameWorld Automation Congress Proceedings
ISSN (Print)2154-4824
ISSN (Electronic)2154-4832

Conference

Conference2014 World Automation Congress, WAC 2014
CountryUnited States
CityWaikoloa
Period14/8/314/8/7

ASJC Scopus subject areas

  • Control and Systems Engineering

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