Local Background Enclosure for RGB-D Salient Object Detection

David Feng, Nick Barnes, Shaodi You, Chris McCarthy; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2343-2350

Abstract


Recent work in salient object detection has considered the incorporation of depth cues from RGB-D images. In most cases, depth contrast is used as the main feature. However, areas of high contrast in background regions cause false positives for such methods, as the background frequently contains regions that are highly variable in depth. Here, we propose a novel RGB-D saliency feature. Local Background Enclosure (LBE) captures the spread of angular directions which are background with respect to the candidate region and the object that it is part of. We show that our feature improves over state-of-the-art RGB-D saliency approaches as well as RGB methods on the RGBD1000 and NJUDS2000 datasets.

Related Material


[pdf]
[bibtex]
@InProceedings{Feng_2016_CVPR,
author = {Feng, David and Barnes, Nick and You, Shaodi and McCarthy, Chris},
title = {Local Background Enclosure for RGB-D Salient Object Detection},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2016}
}