Iterative roll angle estimation from dense disparity map

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...

Full description

Saved in:
Bibliographic Details
Published in2018 7th Mediterranean Conference on Embedded Computing (MECO) pp. 1 - 4
Main Authors Evans, Meghan, Fan, Rui, Dahnoun, Naim
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2018
Subjects
Cameras
Embedded computing
Estimation
Fans
Histograms
Roads
Online AccessGet full text

Cover

More Information
Summary: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.
DOI:10.1109/MECO.2018.8405974