Iterative roll angle estimation from dense disparity map

Meghan C Evans, Rui Fan, Naim Dahnoun

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

6 Citations (Scopus)
142 Downloads (Pure)

Abstract

The v-disparity map is predominantly used to estimate the parameters of the vertical profile of the road surface. Once the road surface is modelled, an object that lies away from it can be detected and determined as either an obstacle or a pothole. The accuracy of this estimation is largely affected by the clarity of the v-disparity map which can be vastly improved by eliminating the effect of a non-zero roll angle. With a rotation around the roll angle for the disparity map, a better v-disparity histogram can be provided. This paper presents a method for accurate roll angle estimation through analysis of the disparity and v-disparity maps. Since the quality of the v-disparity map is improved by rotating the disparity map by the estimated roll angle, this leads to improved road modelling. The more accurate the roll angle estimation, the larger this improvement is.

Original languageEnglish
Title of host publication2018 7th Mediterranean Conference on Embedded Computing (MECO 2018)
Subtitle of host publicationProceedings of a meeting held 10-14 June 2018, Budva, Montenegro
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages488-491
Number of pages4
ISBN (Electronic)9781538656822
ISBN (Print)9781538656846
DOIs
Publication statusPublished - Aug 2018
Event7th Mediterranean Conference on Embedded Computing, MECO 2018: MECO 2018 - Budva, Montenegro
Duration: 10 Jun 201814 Jun 2018

Publication series

Name
ISSN (Print)2377-5475

Conference

Conference7th Mediterranean Conference on Embedded Computing, MECO 2018
CountryMontenegro
CityBudva
Period10/06/1814/06/18

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