Saliency-based object discovery on RGB-D data with a late-fusion approach

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 2015-June, Issue June, 2015, Pages 1866-1873

  Garcia, German M ^a   Potapova, Ekaterina ^b   Werner, Thomas ^a   Zillich, Michael ^b   Vincze, Markus ^b   Frintrop, Simone ^a  

^a UNIVERSITY OF BONN   (Germany)

^b VIENNA UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL ROBOTS; IMAGE SEGMENTATION;

LATE FUSION; REAL-WORLD; SALIENT REGIONS; SEGMENTATION ALGORITHMS; STATE-OF-THE-ART METHODS;

ROBOTICS;

EID: 84938233189     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICRA.2015.7139441     Document Type: Conference Paper

References (29)

1. R. Adams and L. Bischof. Seeded Region Growing. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 16(6):641-647, 1994.
2. B. Alexe, T. Deselaers, and V. Ferrari. Measuring the Objectness of Image Windows. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 34(11):2189-2202, 2012.
3. Chih-Chung Chang and Chih-Jen Lin. Libsvm: A library for support vector machines. ACM Trans. Intell. Syst. Technol., 2(3):1-27, May 2011.
4. Alvaro Collet, Bo Xiong, Corina Gurau, Martial Hebert, and Siddhartha S. Srinivasa. Exploiting Domain Knowledge for Object Discovery. In IEEE International Conference on Robotics and Automation (ICRA), 2013.
5. P. F. Felzenszwalb and D. P. Huttenlocher. Efficient Graph-Based Image Segmentation. International Journal of Computer Vision (IJCV), 59(2), 2004.
6. Jie Feng, Yichen Wei, Litian Tao, Chao Zhang, and Jian Sun. Salient Object Detection by Composition. In IEEE International Conference on Computer Vision ICCV, pages 1028-1035, 2011.
7. Simone Frintrop. VOCUS: A Visual Attention System for Object Detection and Goal-directed Search, volume 3899 of Lecture Notes in Artificial Intelligence (LNAI) (PhD thesis). Springer, 2006.
8. Simone Frintrop, Germán Martín Garcá, and Armin B Cremers. A cognitive approach for object discovery. In ICPR, 2014.
9. Germán Martín Garcá and Simone Frintrop. A Computational Framework for Attentional 3D Object Detection. In Proc. of the Annual Conf. of the Cognitive Science Society, 2013.
10. Germán Martín Garcá, Simone Frintrop, and Armin B. Cremers. Attention-based Detection of Unknown Objects in a Situated Vision Framework. German Journal of Artificial Intelligenz, Springer, 2013.
11. E. Herbst, P. Henry, X. Ren, and D. Fox. Toward object discovery and modeling via 3-d scene comparison. In IEEE International Conference on Robotics and Automation (ICRA), 2011.
12. Ming-Kuei Hu. Visual pattern recognition by moment invariants. IRE Transactions on Information Theory, 8(2):179-187, 1962.
13. L. Itti, C. Koch, and E. Niebur. A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. on Pattern Analysis and Machine Intelligence, 20(11):1254-1259, 1998.
14. M. Johnson-Roberson, J. Bohg, M. Björkman, and D. Kragic. Attention-based Active 3D Point Cloud Segmentation. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2010.
15. A. Karpathy, S. Miller, and L. Fei-Fei. Object discovery in 3D scenes via shape analysis. In IEEE International Conference on Robotics and Automation (ICRA), 2013.
16. Dov Katz, Moslem Kazemi, J. Andrew Bagnell, and Anthony Stentz. Interactive segmentation, tracking, and kinematic modeling of unknown 3D articulated objects. In IEEE International Conference on Robotics and Automation (ICRA), 2013.
17. Kevin Lai, Liefeng Bo, and Dieter Fox. Unsupervised feature learning for 3d scene labeling. In IEEE International Conference on Robotics and Automation (ICRA), 2014.
18. Kevin Lai, Liefeng Bo, Xiaofeng Ren, and Dieter Fox. A large-scale hierarchical multi-view RGB-D object dataset. In IEEE International Conference on Robotics and Automation (ICRA), 2011.
19. S. Manén, M. Guillaumin, and L. Van Gool. Prime Object Proposals with Randomized Prim's Algorithm. In IEEE International Conference on Computer Vision (ICCV), 2013.
20. A David Milner and Melvyn A Goodale. Two visual systems reviewed. Neuropsychologia, 46(3):774-785, 2008.
21. Ajay K. Mishra and Yiannis Aloimonos. Visual Segmentation of Simple Objects for Robots. In Robotics: Science and Systems (RSS), 2011.
22. Jeremie Papon, Alexey Abramov, Markus Schoeler, and Florentin Wörgötter. Voxel cloud connectivity segmentation-supervoxels for point clouds. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
23. Ekaterina Potapova, Karthik M Varadarajan, Andreas Richtsfeld, Michael Zillich, and Markus Vincze. Attention-driven object detection and segmentation of cluttered table scenes using 2. 5D symmetry. In IEEE International Conference on Robotics and Automation (ICRA), 2014.
24. Esa Rahtu, Juho Kannala, and Matthew B. Blaschko. Learning a Category Independent Object Detection Cascade. In IEEE International Conference on Computer Vision, ICCV, pages 1052-1059, 2011.
25. R. A. Rensink. The Dynamic Representation of Scenes. Visual Cognition, 7:17-42, 2000.
26. Andreas Richtsfeld, Thomas Morwald, Johann Prankl, Michael Zillich, and Markus Vincze. Segmentation of unknown objects in indoor environments. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012.
27. M. Ruhnke, B. Steder, G. Grisetti, and W. Burgard. Unsupervised Learning of 3D Object Models from Partial Views. In IEEE International Conference on Robotics and Automation (ICRA), 2009.
28. D. Schiebener, A. Ude, and T. Asfour. Physical Interaction for Segmentation of Unknown Textured and Non-textured Rigid Objects. In IEEE International Conference on Robotics and Automation (ICRA), 2014.
29. B. J. Scholl. Objects and Attention: the State of the Art. Cognition, 80:1-46, 2001.