Hierarchical Salient Object Detection for Assisted Grasping
Computer Vision and Pattern Recognition
2017-01-18 v2 Robotics
Abstract
Visual scene decomposition into semantic entities is one of the major challenges when creating a reliable object grasping system. Recently, we introduced a bottom-up hierarchical clustering approach which is able to segment objects and parts in a scene. In this paper, we introduce a transform from such a segmentation into a corresponding, hierarchical saliency function. In comprehensive experiments we demonstrate its ability to detect salient objects in a scene. Furthermore, this hierarchical saliency defines a most salient corresponding region (scale) for every point in an image. Based on this, an easy-to-use pick and place manipulation system was developed and tested exemplarily.
Cite
@article{arxiv.1701.04284,
title = {Hierarchical Salient Object Detection for Assisted Grasping},
author = {Dominik Alexander Klein and Boris Illing and Bastian Gaspers and Dirk Schulz and Armin Bernd Cremers},
journal= {arXiv preprint arXiv:1701.04284},
year = {2017}
}
Comments
Accepted for ICRA 2017