Segmentation of Salient Regions in Outdoor Scenes Using Imagery and 3-D Data - Robotics Institute Carnegie Mellon University

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

Workshop Paper, IEEE Workshop on Applications of Computer Vision (WACV '08), 2008

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

@workshop{Kim-2008-9886,
author = {Gunhee Kim and Daniel Huber and Martial Hebert},
title = {Segmentation of Salient Regions in Outdoor Scenes Using Imagery and 3-D Data},
booktitle = {Proceedings of IEEE Workshop on Applications of Computer Vision (WACV '08)},
year = {2008},
month = {January},
publisher = {IEEE Computer Society},
keywords = {Computer Vision, LADAR, Saliency, Segmentation},
}