An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database

Sensors
Yan LiYang Gao

Abstract

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and ...Continue Reading

References

Jun 30, 2011·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Yinan YuTieniu Tan
Dec 14, 2011·Sensors·Jiann-Yeou RauYu-Hua Li
Sep 13, 2012·Sensors·Luis A GuerreroSergio F Ochoa
Oct 17, 2015·Sensors·Qidan ZhuChengtao Cai

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Software Mentioned

Inertial Explorer
Topcon
Hi
GRID
Google Street View
Windows XP
Tencent Panoramic Image Service
Target iScan

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