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Sensors 2015, 15(9), 21636-21659; doi:10.3390/s150921636

A Probabilistic Feature Map-Based Localization System Using a Monocular Camera

1
Urban Robotics Laboratory (URL), Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro (373-1 Guseong-dong), Yuseong-gu, Daejeon 305-701, Korea
2
Ocean System Engineering Research Division, Korea Research Institute of Ships and Ocean Engineering (KRISO), 32 1312 Beon-gil, Yuseong-daero, Yuseong-gu, Daejeon 305-343, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Kourosh Khoshelham
Received: 27 April 2015 / Revised: 23 August 2015 / Accepted: 24 August 2015 / Published: 31 August 2015
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
View Full-Text   |   Download PDF [2341 KB, uploaded 31 August 2015]   |  

Abstract

Image-based localization is one of the most widely researched localization techniques in the robotics and computer vision communities. As enormous image data sets are provided through the Internet, many studies on estimating a location with a pre-built image-based 3D map have been conducted. Most research groups use numerous image data sets that contain sufficient features. In contrast, this paper focuses on image-based localization in the case of insufficient images and features. A more accurate localization method is proposed based on a probabilistic map using 3D-to-2D matching correspondences between a map and a query image. The probabilistic feature map is generated in advance by probabilistic modeling of the sensor system as well as the uncertainties of camera poses. Using the conventional PnP algorithm, an initial camera pose is estimated on the probabilistic feature map. The proposed algorithm is optimized from the initial pose by minimizing Mahalanobis distance errors between features from the query image and the map to improve accuracy. To verify that the localization accuracy is improved, the proposed algorithm is compared with the conventional algorithm in a simulation and realenvironments View Full-Text
Keywords: localization; monocular camera; probabilistic feature map; 3D-to-2D matching correspondences; image data set localization; monocular camera; probabilistic feature map; 3D-to-2D matching correspondences; image data set
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kim, H.; Lee, D.; Oh, T.; Choi, H.-T.; Myung, H. A Probabilistic Feature Map-Based Localization System Using a Monocular Camera. Sensors 2015, 15, 21636-21659.

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