Skip to main content
placeholder image

Pedestrian lane detection in unstructured scenes for assistive navigation

Journal Article


Download full-text (Open Access)

Abstract


  • Automatic detection of the pedestrian lane in a scene is an important task in assistive and autonomous navigation. This paper presents a vision-based algorithm for pedestrian lane detection in unstructured scenes, where lanes vary significantly in color, texture, and shape and are not indicated by any painted markers. In the proposed method, a lane appearance model is constructed adaptively from a sample image region, which is identified automatically from the image vanishing point. This paper also introduces a fast and robust vanishing point estimation method based on the color tensor and dominant orientations of color edge pixels. The proposed pedestrian lane detection method is evaluated on a new benchmark dataset that contains images from various indoor and outdoor scenes with different types of unmarked lanes. Experimental results are presented which demonstrate its efficiency and robustness in comparison with several existing methods.

Publication Date


  • 2016

Citation


  • S. Phung, M. Cuong. Le & A. Bouzerdoum, "Pedestrian lane detection in unstructured scenes for assistive navigation," Computer Vision and Image Understanding, vol. 149, pp. 186-196, 2016.

Scopus Eid


  • 2-s2.0-84991047698

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=7236&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/6206

Number Of Pages


  • 10

Start Page


  • 186

End Page


  • 196

Volume


  • 149

Abstract


  • Automatic detection of the pedestrian lane in a scene is an important task in assistive and autonomous navigation. This paper presents a vision-based algorithm for pedestrian lane detection in unstructured scenes, where lanes vary significantly in color, texture, and shape and are not indicated by any painted markers. In the proposed method, a lane appearance model is constructed adaptively from a sample image region, which is identified automatically from the image vanishing point. This paper also introduces a fast and robust vanishing point estimation method based on the color tensor and dominant orientations of color edge pixels. The proposed pedestrian lane detection method is evaluated on a new benchmark dataset that contains images from various indoor and outdoor scenes with different types of unmarked lanes. Experimental results are presented which demonstrate its efficiency and robustness in comparison with several existing methods.

Publication Date


  • 2016

Citation


  • S. Phung, M. Cuong. Le & A. Bouzerdoum, "Pedestrian lane detection in unstructured scenes for assistive navigation," Computer Vision and Image Understanding, vol. 149, pp. 186-196, 2016.

Scopus Eid


  • 2-s2.0-84991047698

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=7236&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/6206

Number Of Pages


  • 10

Start Page


  • 186

End Page


  • 196

Volume


  • 149