|
|
|
|
| LEADER |
01000naa a22002652 4500 |
| 001 |
NLM327789360 |
| 003 |
DE-627 |
| 005 |
20231225201549.0 |
| 007 |
cr uuu---uuuuu |
| 008 |
231225s2021 xx |||||o 00| ||eng c |
| 024 |
7 |
|
|a 10.1109/TIP.2021.3093789
|2 doi
|
| 028 |
5 |
2 |
|a pubmed24n1092.xml
|
| 035 |
|
|
|a (DE-627)NLM327789360
|
| 035 |
|
|
|a (NLM)34232878
|
| 040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
| 041 |
|
|
|a eng
|
| 100 |
1 |
|
|a Gao, Feng
|e verfasserin
|4 aut
|
| 245 |
1 |
0 |
|a MGG
|b Monocular Global Geolocation for Outdoor Long-Range Targets
|
| 264 |
|
1 |
|c 2021
|
| 336 |
|
|
|a Text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
| 338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
| 500 |
|
|
|a Date Revised 14.07.2021
|
| 500 |
|
|
|a published: Print-Electronic
|
| 500 |
|
|
|a Citation Status PubMed-not-MEDLINE
|
| 520 |
|
|
|a Traditional monocular vision localization methods are usually suitable for short-range area and indoor relative positioning tasks. This paper presents MGG, a novel monocular global geolocation method for outdoor long-range targets. This method takes a single RGB image combined with necessary navigation parameters as input and outputs targets' GPS information under the Global Navigation Satellite System (GNSS). In MGG, we first design a camera pose correction method via pixel mapping to correct the pose of the camera. Then, we use anchor-based methods to improve the detection ability for long-range targets with small image regions. Next, the local monocular vision model (LMVM) with a local structure coefficient is proposed to establish an accurate 2D-to-3D mapping relationship. Subsequently, a soft correspondence constraint (SCC) is presented to solve the local structure coefficient, which can weaken the coupling degree between detection and localization. Finally, targets can be geolocated through optimization theory-based methods and a series of coordinate transformations. Furthermore, we demonstrate the importance of focal length on solving the error explosion problem in locating long-range targets with monocular vision. Extensive experiments on the challenging KITTI dataset as well as applications in outdoor environments with targets located at a long range of up to 150 meters show the superiority of our method
|
| 650 |
|
4 |
|a Journal Article
|
| 700 |
1 |
|
|a Deng, Fang
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Li, Linhan
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Zhang, Lele
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Zhu, Jiaqi
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Yu, Chengpu
|e verfasserin
|4 aut
|
| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 30(2021) vom: 07., Seite 6349-6363
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
|
| 773 |
1 |
8 |
|g volume:30
|g year:2021
|g day:07
|g pages:6349-6363
|
| 856 |
4 |
0 |
|u http://dx.doi.org/10.1109/TIP.2021.3093789
|3 Volltext
|
| 912 |
|
|
|a GBV_USEFLAG_A
|
| 912 |
|
|
|a SYSFLAG_A
|
| 912 |
|
|
|a GBV_NLM
|
| 912 |
|
|
|a GBV_ILN_350
|
| 951 |
|
|
|a AR
|
| 952 |
|
|
|d 30
|j 2021
|b 07
|h 6349-6363
|