Hierarchical Salient Object Detection for Assisted Grasping

January 16, 2017 Β· Declared Dead Β· πŸ› 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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