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

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journal contribution
posted on 01.01.2008, 00:00 authored by Gunhee Kim, Daniel F. Huber, Martial Hebert
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.


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