Zebra-crossing detection for the partially sighted

Zebra-crossings are useful road features for outdoor navigation in mobility aids for the partially sighted. In this paper, zebra-crossings are detected by looking for groups of concurrent lines, edges are then partitioned using intensity variation information. In order to tackle the ambiguity of the detection algorithm in distinguishing zebra-crossings and stair-cases, pose information is sought. Three methods are developed to estimate the pose: homography search approach using an a priori model; finding normal using the vanishing line computed from equally-spaced lines and with two vanishing points. These algorithms have been applied to real images with promising results and they are also useful in some other shape from texture applications.

[1]  Andrew Zisserman,et al.  Geometric Grouping of Repeated Elements within Images , 1998, BMVC.

[2]  David Lee,et al.  Robotic Sensing for the Guidance of the Visually Impaired , 1998 .

[3]  J. Garding,et al.  Shape from texture and contour by weak isotropy , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[4]  Penny Probert Smith,et al.  Robotic sensing for the partially sighted , 1999, Robotics Auton. Syst..

[5]  Jake K. Aggarwal,et al.  Determining vanishing points from perspective images , 1984, Comput. Vis. Graph. Image Process..

[6]  Robert T. Collins,et al.  Vanishing point calculation as a statistical inference on the unit sphere , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[7]  Andrew Blake,et al.  Shape from Texture: Estimation, Isotropy and Moments , 1990, Artif. Intell..

[8]  Michael Brady,et al.  Vision-based Detection of Kerbs and Steps , 1997, BMVC.

[9]  Sven Utcke Grouping based on projective geometry constraints and uncertainty , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[10]  Kenichi Kanatani,et al.  Detection of Surface Orientation and Motion from Texture by a Stereological Technique , 1984, Artif. Intell..

[11]  R. Hetherington The Perception of the Visual World , 1952 .

[12]  Long Quan,et al.  Determining perspective structures using hierarchical Hough transform , 1989, Pattern Recognit. Lett..

[13]  Stephen T. Barnard,et al.  Interpreting Perspective Image , 1983, Artif. Intell..

[14]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[15]  A. U.S.,et al.  Recovering Surface Shape and Orientation from Texture , 2002 .

[16]  Luc Van Gool,et al.  The cascaded Hough transform as an aid in aerial image interpretation , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[17]  Beatrice Brillault-O'Mahony,et al.  New method for vanishing point detection , 1991, CVGIP Image Underst..

[18]  Jonas Ghding Shape from Texture and Contour by Weak Isotropy , 1990 .

[19]  O. Faugeras Three-dimensional computer vision: a geometric viewpoint , 1993 .

[20]  Penny Probert Smith,et al.  A stereo vision-based aid for the visually impaired , 1998, Image Vis. Comput..