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Hierarchical salient object detection for assisted grasping

: Klein, D.A.; Illing, B.; Gaspers, B.; Schulz, D.; Cremers, A.B.


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Robotics and Automation Society:
IEEE International Conference on Robotics and Automation, ICRA 2017 : May 29-June 3, 2017, Singapore
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5090-4633-1
ISBN: 978-1-5090-4634-8 (Print)
International Conference on Robotics and Automation (ICRA) <2017, Singapore>
Conference Paper
Fraunhofer FKIE ()

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 [1] 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.