Efficient Vanishing Point Estimation for Unstructured Road Scenes

Linh Nguyen, Son Lam Phung, Abdesselam Bouzerdoum

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Vanishing point estimation is an essential and demanding task in vision-based road detection. One of the main limitations of the existing approaches for vanishing point estimation is computation efficiency, which hampers their real-time applications. This paper presents an efficient method for finding the vanishing point in unstructured road scenes. Color tensors are applied on the input image to find texture orientations and color edges. We propose new strategies to select optimized sets of vanishing point candidates and voters and to define the voting function. The proposed method is evaluated on a benchmark dataset of 2000 images of unmarked pedestrian lanes. The experimental results show that it achieves accuracy comparable with other state-of-the-art methods but with significantly reduced computation time.

Original languageEnglish
Title of host publication2016 International Conference on Digital Image Computing
Subtitle of host publicationTechniques and Applications, DICTA 2016
EditorsAlan Wee-Chung Liew, Jun Zhou, Yongsheng Gao, Zhiyong Wang, Clinton Fookes, Brian Lovell, Michael Blumenstein
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509028962
DOIs
Publication statusPublished - 22 Dec 2016
Externally publishedYes
Event2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016 - Gold Coast, Australia
Duration: 30 Nov 20162 Dec 2016

Publication series

Name2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016

Conference

Conference2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016
Country/TerritoryAustralia
CityGold Coast
Period30/11/162/12/16

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