Hierarchical Salient Object Detection for Assisted Grasping
January 16, 2017 Β· Declared Dead Β· π IEEE International Conference on Robotics and Automation
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Authors
Dominik Alexander Klein, Boris Illing, Bastian Gaspers, Dirk Schulz, Armin Bernd Cremers
arXiv ID
1701.04284
Category
cs.CV: Computer Vision
Cross-listed
cs.RO
Citations
7
Venue
IEEE International Conference on Robotics and Automation
Last Checked
4 months ago
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.
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