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Reseach Article

Nested Graph Representation for Visual SLAM based on Local and Global Feature Processing

by Sara Elgayar, Mohammed A.-m. Salem, Mohamed I. Roushdy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 78 - Number 16
Year of Publication: 2013
Authors: Sara Elgayar, Mohammed A.-m. Salem, Mohamed I. Roushdy
10.5120/13604-1350

Sara Elgayar, Mohammed A.-m. Salem, Mohamed I. Roushdy . Nested Graph Representation for Visual SLAM based on Local and Global Feature Processing. International Journal of Computer Applications. 78, 16 ( September 2013), 1-8. DOI=10.5120/13604-1350

@article{ 10.5120/13604-1350,
author = { Sara Elgayar, Mohammed A.-m. Salem, Mohamed I. Roushdy },
title = { Nested Graph Representation for Visual SLAM based on Local and Global Feature Processing },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 78 },
number = { 16 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume78/number16/13604-1350/ },
doi = { 10.5120/13604-1350 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:42.345747+05:30
%A Sara Elgayar
%A Mohammed A.-m. Salem
%A Mohamed I. Roushdy
%T Nested Graph Representation for Visual SLAM based on Local and Global Feature Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 78
%N 16
%P 1-8
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Self localization of mobile autonomous systems is fundamental step in various applications, such as assistant navigation systems for blind people or smart house appliances. This paper presents a novel framework for Vision-based Simultaneous Localization and Mapping which focuses on the class of indoor mobile robots using only a monocular camera. A method to combine local and global features mapping have been proposed in a nested graph representation, where the indoor environment is divided into locations which is then decomposed into different views. The Scale Invariant Feature Transform is used to extract and build up a global map which provide rough estimation of the robot position. Horizontal, vertical and diagonal details of the wavelet coefficients are then used to provide finer estimation of the robot position and pose. The output topological map is validated with the ground truth of the environment. Moreover, the number of decomposition levels of the wavelet transform is analysed. The results show high localization accuracy and low rate of matching time.

References
  1. Mariam Al-Berry, Mohammed A. -Megeed Salem, A S. Hussein, and M. F. Tolba. Spatio-temporal motion de-tection for intelligent surveillance applications. submitted to the International Journal of Computer Mathematics, 2013.
  2. J. -L. Blanco, J. -A. Fernandez-Madrigal, and J. Gonzalez. Toward a unified bayesian approach to hybrid metric–topological slam. Robotics, IEEE Tr. on, 24(2):259–270, 2008.
  3. Ingrid Daubechies. Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, 1992.
  4. Andrew J Davison, Ian D Reid, Nicholas D Molton, and Olivier Stasse. Monoslam: Real-time single camera slam. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 29(6):1052–1067, 2007.
  5. Sara Elgayar, Mohammed A. -Megeed Salem, and Mohamed I. Roushdy. Two-level topological mapping and localization based on sift and the wavelet transform. In 2nd International Conference on Circuits, Systems, Communications, Computers and Applications, Dubrovnik, Croatia, June 25-27 2013.
  6. J. Guivant, J. I. Nieto, and E Nebot. The hybrid metric maps (hymms): A novel map representation for denseslam. In Proceedings of IEEE 2004 Int. Conf. on Robotics and Automation, 26 Apr. - 01 May 2004.
  7. Gerald Kaiser. The fast haar transform, gateway to wavelets. IEEE potentials, April-May 1998.
  8. Kohavi and Provost. Confusion matrix, 1998.
  9. Thomas Lemaire, Cyrille Berger, Il-Kyun Jung, and Simon Lacroix. Vision-based slam: Stereo and monocular approaches. International Journal of Computer Vision, 74(3):343–364, 2007.
  10. David G Lowe. Distinctive image features from scaleinvariant keypoints. Int. Jo. of Computer Vision, 60(2):91–110, 2004.
  11. Wen Lik Dennis Lui and Ray Jarvis. A pure visionbased topological slam system. The International Journal of Robotics Research, 31(4):403–428, 2012.
  12. Stéphane G. Mallat. A theory for multiresolution signal decomposition, the wavelet representation. IEEE Tr. on Pattern Analysis and Machine Intelligence, 2(7):674– 693, 1989.
  13. Jesus Martinez-Gomez, Alejando Jimenez-Picazo, Jose A. Gomez, and Ismael Garcia-Varea. Combining invariant features and localization techniques for visual place classification: successful experiences in the robotvision@imageclef competition. Journal of Physical Agents, 5(1), January 2011.
  14. M. Mata, J. M. Armingol, A. De La Escalera, and M. A. Salichs. Using learned visual landmarks for intelligent topological navigation of mobile robots. In IEEE Int. Conf. on Robotics and Automation, 2003.
  15. Ana Cris Murillo, JJ Guerrero, and C Sagues. Surf features for efficient robot localization with omnidirectional images. In Robotics and Automation, 2007 IEEE International Conference on, pages 3901–3907. IEEE, 2007.
  16. Muhammad Naveed, David Fofi, and Samia Ainouz. Vision Based Simultaneous Localisation and Mapping for Mobile Robots. PhD thesis, MasterŠs Thesis, Universit de Bourgogne, 2008.
  17. Richard A Newcombe and Andrew J Davison. Live dense reconstruction with a single moving camera. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, pages 1498–1505. IEEE, 2010.
  18. Vivek Pradeep, Gérard G. Medioni, and James Weiland. Visual loop closing using multi-resolution sift grids in metric-topological slam. In CVPR, pages 1438– 1445, 2009.
  19. Alberto Pretto, Emanuele Menegatti, Yoshiaki Jitsukawa, Ryuichi Ueda, and Tamio Arai. Image similarity based on discrete wavelet transform for robots with low-computational resources. Robotics and Autonomous Systems, 58(7):879–888, 2010.
  20. Andrzej Pronobis. The cold-stockholm database, 2009.
  21. Mohammed A. -M. Salem. Medical Image Segmentation: Multiresolution-based Algorithms. VDM Verlag, Dr. Mueller, 2011.
  22. Mohammed A. -M. Salem. On the selection of the proper wavelet for moving object detection. In The 7th IEEE Int. Conf. on Computer Engineering and Systems, Cairo, Egypt, November 29-30, December 1 2011.
  23. Mohammed A. -M. Salem. Multi-stage localization given topological map for autonomous robots. In The 8th IEEE Int. Conf. on Computer Engineering and Systems, Cairo, Egypt, Nov. 29-30, Dec. 1 2012.
  24. Stephen Se, David G Lowe, and James J Little. Vision-based global localization and mapping for mobile robots. Robotics, IEEE Transactions on, 21(3):364– 375, 2005.
  25. Bruno Siciliano and Oussama Khatib, editors. Springer Handbook of Robotics. Springer, 2008.
  26. Robert Sim, Pantelis Elinas, Matt Griffin, and James J Little. Vision-based slam using the rao-blackwellised particle filter. In IJCAI Workshop on Reasoning with Uncertainty in Robotics, volume 14, pages 9–16, 2005.
  27. Cyrill Stachniss. Robotic mapping and exploration, volume 55. Springer, 2009.
  28. Mohamed A. Tahoun, Khaled A. Nagaty, Taha I. El- Arief, and Mohammed A. -Megeed Salem. A robust content-based image retrieval system using multiple features representations. In IEEE Int. Conf. on Networking, Sensing and Control, Arizona, USA, Mar. 19- 22 2005.
  29. S. Thrun, D. Hähnel, D. Ferguson, M. Montemerlo, R. Triebel, W. Burgard, C. Baker, Z. Omohundro, S. Thayer, and W. Whittaker. A system for volumetric robotic mapping of abandoned mines. In Proceedings of the IEEE Int. Con. on Robotics and Automation, 2003.
  30. Iwan Ulrich and Illah Nourbakhsh. Appearance-based place recognition for topological localization. In Int. Conf. on Robotics and Automation, ICRA'00, pages 1023–1029, San Francisco, USA, 2000.
  31. Hanafiah Yussof, editor. Robot Localization and Map Building. InfoTech, Berlin, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Robot Vision Local Features Global Features SIFT Wavelet Transform Topological Map