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Enhanced pixel-wise voting for image vanishing point detection in road scenes

Conference Paper


Abstract


  • Vanishing point estimation is a crucial task in vision-based road detection. This paper presents a new texture-based voting scheme, which enhances both accuracy and speed of vanishing point estimation. In the proposed method, color tensors analysis is adopted to calculate local orientations and color edges. The search space is reduced by optimizing the set of vanishing point candidates and voters. A new strategy based on Bayesian classifier is proposed to select a suitable voting function. The proposed method is evaluated on a benchmark dataset of 4000 images of pedestrian lanes with annotated vanishing points. The experimental results show that it offers an improved accuracy and significantly faster processing time compared with other state-of-the-art methods.

Publication Date


  • 2017

Citation


  • L. Nguyen, S. L. Phung & A. Bouzerdoum, "Enhanced pixel-wise voting for image vanishing point detection in road scenes," in 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017, pp. 1852-1856.

Scopus Eid


  • 2-s2.0-85023782660

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/477

Start Page


  • 1852

End Page


  • 1856

Place Of Publication


  • New York, United States

Abstract


  • Vanishing point estimation is a crucial task in vision-based road detection. This paper presents a new texture-based voting scheme, which enhances both accuracy and speed of vanishing point estimation. In the proposed method, color tensors analysis is adopted to calculate local orientations and color edges. The search space is reduced by optimizing the set of vanishing point candidates and voters. A new strategy based on Bayesian classifier is proposed to select a suitable voting function. The proposed method is evaluated on a benchmark dataset of 4000 images of pedestrian lanes with annotated vanishing points. The experimental results show that it offers an improved accuracy and significantly faster processing time compared with other state-of-the-art methods.

Publication Date


  • 2017

Citation


  • L. Nguyen, S. L. Phung & A. Bouzerdoum, "Enhanced pixel-wise voting for image vanishing point detection in road scenes," in 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2017, pp. 1852-1856.

Scopus Eid


  • 2-s2.0-85023782660

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/477

Start Page


  • 1852

End Page


  • 1856

Place Of Publication


  • New York, United States