Authors:
Carsten Høilund
1
;
Thomas B. Moeslund
1
;
Claus B. Madsen
1
and
Mohan M. Trivedi
2
Affiliations:
1
Aalborg University, Denmark
;
2
University of California, San Diego, United States
Keyword(s):
Free space, Stereo vision, Kalman filtering, Stochastic occupancy grid.
Related
Ontology
Subjects/Areas/Topics:
Active and Robot Vision
;
Computer Vision, Visualization and Computer Graphics
;
Image Filtering
;
Image Formation and Preprocessing
;
Motion, Tracking and Stereo Vision
;
Stereo Vision and Structure from Motion
;
Visual Navigation
Abstract:
This paper presents a method for determining the free space in a scene as viewed by a vehicle-mounted camera. Using disparity maps from a stereo camera and known camera motion, the disparity maps are first filtered by an iconic Kalman filter, operating on each pixel individually, thereby reducing variance and increasing the density of the filtered disparity map. Then, a stochastic occupancy grid is calculated from the filtered disparity map, providing a top-down view of the scene where the uncertainty of disparity measurements are taken into account. These occupancy grids are segmented to indicate a maximum depth free of obstacles, enabling the marking of free space in the accompanying intensity image. The test shows successful marking of free space in the evaluated scenarios in addition to significant improvement in disparity map quality.