Title :
Segmentation of occluded sidewalks in satellite images
Author :
Senlet, Turgay ; Elgammal, Ahmed
Author_Institution :
Dept. of Comput. Sci. Rutgers, Rutgers, State Univ. of New Jersey, Piscataway, NJ, USA
Abstract :
Accurate segmentation of sidewalks from satellite images can be required in various applications, for example giving walking directions to pedestrians and robot navigation. We propose a framework to construct sidewalk and crosswalk maps from satellite images. This is a challenging task, since typically sidewalks in satellite images are highly occluded by trees and their shadows and also there can be several objects on maps that have similar appearance with sidewalks. In our framework, we initially segment visible sidewalks by their appearance and then complete the tree-occluded areas by posing the problem as an image-inpainting task with multiple priors, which fuses the knowledge about roads, occluders and sidewalk structures. We present successful sidewalk segmentation results from satellite images, where sidewalks are highly occluded by trees.
Keywords :
geophysical image processing; image fusion; image segmentation; pedestrians; crosswalk map construction; image inpainting; knowledge fusion; occluded sidewalk segmentation; pedestrians; robot navigation; satellite images; sidewalk map construction; tree-occluded areas; visible sidewalk segmentation; walking directions; Buildings; Image color analysis; Image segmentation; Roads; Robots; Satellites; Vegetation;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4