Authors:
Kazuki Goro
and
Kazunori Onoguchi
Affiliation:
Hirosaki University, Japan
Keyword(s):
Inverse Perspective Mapping, ITS, Shoulder of a Road, Snow Wall, Snakes.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Image Understanding
;
Pattern Recognition
;
Robotics
;
Software Engineering
Abstract:
When a lane marker such as a white line is not drawn on the road or it’s hidden by snow, it’s important for
the lateral motion control of the vehicle to detect the boundary line between the road and the roadside object
such as curbs, grasses, side walls and so on. Especially, when the road is covered with snow, it’s necessary to
detect the boundary between the snow side wall and the road because other roadside objects are occluded by
snow. In this paper, we proposes the novel method to detect the shoulder line of a road including the boundary
with the snow side wall from an image of an in-vehicle monocular camera. Vertical lines on an object whose
height is different from a road surface are projected onto slanting lines when an input image is mapped to a
road surface by the inverse perspective mapping. The proposed method detects a road boundary using this
characteristic. In order to cope with the snow surface where various textures appear, we introduce the degree
of road bo
undary that responds strongly at the boundary with the area where slant edges are dense. Since the
shape of the snow wall is complicated, the boundary line is extracted by the Snakes using the degree of road
boundary as image forces. Experimental results using the KITTI dataset and our own dataset including snow
road show the effectiveness of the proposed method.
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