Overhead-based image and video geo-localization framework

被引：10

作者：

Hammoud, Riad I. ^{[1
]}

Kuzdeba, Scott A. ^{[1
]}

Berard, Brian ^{[1
]}

Tom, Victor ^{[1
]}

Ivey, Richard ^{[1
]}

Bostwick, Renu ^{[1
]}

HandUber, Jason ^{[1
]}

Vinciguerra, Lori ^{[1
]}

Shnidman, Nathan ^{[1
]}

Smiley, Byron ^{[1
]}

机构：

[1] BAE Syst, Burlington, MA 01803 USA

来源：

2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) | 2013年

关键词：

D O I：

10.1109/CVPRW.2013.55

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a geo-localization framework of street-level outdoor images using multiple sources of overhead reference imagery including LIDAR, Digital Elevation Maps and Multi-Spectral Land Cover/Use imagery. We describe five different matchers and an adaptive linear fusion process which combines individual matchers' probability maps into a single map. These matchers exploit mountain elevation profiles, rendered camera views, landmarks, landuse classes and building heights. We successfully validated our framework on 100 queries with geographic truth in two world regions (each of 10, 000km(2)) in the USA.

引用

页码：320 / 327

页数：8

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