When 2.5D is not enough: Simultaneous reconstruction, segmentation and recognition on dense SLAM
Tateno K, Tombari F, Navab N (2016)
Publication Type: Conference contribution
Publication year: 2016
Journal
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2016-June
Pages Range: 2295-2302
Conference Proceedings Title: Proceedings - IEEE International Conference on Robotics and Automation
Event location: Stockholm, SWE
ISBN: 9781467380263
DOI: 10.1109/ICRA.2016.7487378
Abstract
While the main trend of 3D object recognition has been to infer object detection from single views of the scene - i.e., 2.5D data - this work explores the direction on performing object recognition on 3D data that is reconstructed from multiple viewpoints, under the conjecture that such data can improve the robustness of an object recognition system. To achieve this goal, we propose a framework which is able (i) to carry out incremental real-time segmentation of a 3D scene while being reconstructed via Simultaneous Localization And Mapping (SLAM), and (ii) to simultaneously and incrementally carry out 3D object recognition and pose estimation on the reconstructed and segmented 3D representations. Experimental results demonstrate the advantages of our approach with respect to traditional single view-based object recognition and pose estimation approaches, as well as its usefulness in robotic perception and augmented reality applications.
Involved external institutions
Germany (DE)How to cite
APA:
Tateno, K., Tombari, F., & Navab, N. (2016). When 2.5D is not enough: Simultaneous reconstruction, segmentation and recognition on dense SLAM. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 2295-2302). Stockholm, SWE: Institute of Electrical and Electronics Engineers Inc..
MLA:
Tateno, Keisuke, Federico Tombari, and Nassir Navab. "When 2.5D is not enough: Simultaneous reconstruction, segmentation and recognition on dense SLAM." Proceedings of the 2016 IEEE International Conference on Robotics and Automation, ICRA 2016, Stockholm, SWE Institute of Electrical and Electronics Engineers Inc., 2016. 2295-2302.
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