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Localization of a Monocular Camera using a Feature-based Probabilistic Map

특징점 기반 확률 맵을 이용한 단일 카메라의 위치 추정방법

  • 김형진 (KAIST 건설 및 환경공학과) ;
  • 이동화 (KAIST 건설 및 환경공학과) ;
  • 오택준 (KAIST 건설 및 환경공학과) ;
  • 명현 (KAIST 건설 및 환경공학과)
  • Received : 2014.11.15
  • Accepted : 2015.02.25
  • Published : 2015.04.01

Abstract

In this paper, a novel localization method for a monocular camera is proposed by using a feature-based probabilistic map. The localization of a camera is generally estimated from 3D-to-2D correspondences between a 3D map and an image plane through the PnP algorithm. In the computer vision communities, an accurate 3D map is generated by optimization using a large number of image dataset for camera pose estimation. In robotics communities, a camera pose is estimated by probabilistic approaches with lack of feature. Thus, it needs an extra system because the camera system cannot estimate a full state of the robot pose. Therefore, we propose an accurate localization method for a monocular camera using a probabilistic approach in the case of an insufficient image dataset without any extra system. In our system, features from a probabilistic map are projected into an image plane using linear approximation. By minimizing Mahalanobis distance between the projected features from the probabilistic map and extracted features from a query image, the accurate pose of the monocular camera is estimated from an initial pose obtained by the PnP algorithm. The proposed algorithm is demonstrated through simulations in a 3D space.

Acknowledgement

Grant : 실외환경에 강인한 도로 기반 저가형 자율주행기술 개발

Supported by : 산업통상자원부

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