Home/Segmentation of Salient Regions in Outdoor Scenes Using Imagery and 3-D Data

Segmentation of Salient Regions in Outdoor Scenes Using Imagery and 3-D Data

Gunhee Kim, Daniel Huber and Martial Hebert
Conference Paper, Carnegie Mellon University, IEEE Workshop on Applications of Computer VIsion (WACV08), January, 2008

Download Publication (PDF)

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

This paper describes a segmentation method for extracting salient regions in outdoor scenes using both 3-D laser scans and imagery information. Our approach is a bottom-up attentive process without any high-level priors, models, or learning. As a mid-level vision task, it is not only robust against noise and outliers but it also provides valuable information for other high-level tasks in the form of optimal segments and their ranked saliency. In this paper, we propose a new saliency definition for 3-D point clouds and we incorporate it with saliency features from color information.

BibTeX Reference
@conference{Kim-2008-9886,
title = {Segmentation of Salient Regions in Outdoor Scenes Using Imagery and 3-D Data},
author = {Gunhee Kim and Daniel Huber and Martial Hebert},
booktitle = {IEEE Workshop on Applications of Computer VIsion (WACV08)},
keyword = {Computer Vision, LADAR, Saliency, Segmentation},
sponsor = {U.S Army Research Laboratory},
publisher = {IEEE Computer Society},
grantID = {DAAD19-01-2-0012},
school = {Robotics Institute , Carnegie Mellon University},
month = {January},
year = {2008},
address = {Pittsburgh, PA},
}
2017-09-13T10:41:53+00:00