Earticle

초록

영어

This paper presents a novel method to generate an index word for the topological map in robot localization. Previous studies extract only appearance features from an input image to match the visual words of the model images. However, the localization performance is much affected by the miss or false matches. First, we segment a robot navigation environment into the structural planes using 3D depth data. We obtain both the surface normal vectors of the structural planes and visual features in the model image, which are compared with those of an input request image in the voting approach. The experimental results show the voting performance is improved by taking into account the spatial distribution of the features.

목차

Abstract
 1. Introduction
 2. Related Works
 3. Proposed Method
  3.1. Plane Segmetation and Visual Word Generation
  3.2. Matching and Localization
 4. Experiments and Discussion
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Sangyun Lee [ Department of Imaging Science and Arts, GSAIM, Chung-Ang University,Seoul,Korea ]
• InPyo Lee [ Department of Imaging Science and Arts, GSAIM, Chung-Ang University,Seoul,Korea ]
• Changkyung Eem [ College of ICT Engineering, Chung-Ang University, Seoul, Korea ]
• Hyunki Hong [ School of Integrative Engineering, Chung-Ang University, Seoul, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605