Conference Proceeding

Reconstruction of a road by local image matches and global 3D optimization

Comput. Vision Lab., Maryland Univ., College Park, MD
06/1990; DOI:10.1109/ROBOT.1990.126186 pp.1337 - 1342 vol.2 In proceeding of: Robotics and Automation, 1990. Proceedings., 1990 IEEE International Conference on
Source: IEEE Xplore

ABSTRACT A method is presented for reconstructing a 3-D road from a single
image. It finds the images of opposite points of the road. Opposite
points are points which face each other on the opposite sides of the
road; the images of these points are called matching points. For points
chosen from one side of the road image, the algorithm finds all the
matching point candidates on the other side, based on local properties
of a road. However, these solutions do not necessarily satisfy the
global properties of a typical road. A dynamic programming algorithm is
applied to reject the candidates which do not fit the global road. A
benchmark using synthetic roads is described. It shows that the roads
reconstructed by the proposed method match the actual roads better than
those reconstructed by two other road reconstruction algorithms.
Experiments with 50 road images taken by the autonomous land vehicle
(ALV) showed that the method is robust with real-world data and that the
reconstructions are fairly consistent with road profiles obtained by
fusion between range images and video images

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Keywords

3-D road
 
50 road images
 
actual roads
 
dynamic programming algorithm
 
global properties
 
global road
 
images
 
local properties
 
point candidates
 
proposed method match
 
range images
 
reconstructing
 
road image
 
road profiles
 
road reconstruction algorithms
 
sides
 
solutions
 
synthetic roads
 
typical road
 
video images
 

D. DeMenthon