2007 IEEE International Geoscience and Remote Sensing Symposium 2007
DOI: 10.1109/igarss.2007.4422884
|View full text |Cite
|
Sign up to set email alerts
|

Towards high accuracy road maps generation from massive GPS Traces data

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
37
0

Year Published

2011
2011
2020
2020

Publication Types

Select...
5
1
1

Relationship

0
7

Authors

Journals

citations
Cited by 72 publications
(38 citation statements)
references
References 2 publications
0
37
0
Order By: Relevance
“…Hence, the κ i values range from [0. 5,1]. If the κ i values are close to 1, then the points have more linear distributions, which means that more of the feature points around x i are aligned along a road.…”
Section: Road Skeleton Segmentationmentioning
confidence: 99%
See 2 more Smart Citations
“…Hence, the κ i values range from [0. 5,1]. If the κ i values are close to 1, then the points have more linear distributions, which means that more of the feature points around x i are aligned along a road.…”
Section: Road Skeleton Segmentationmentioning
confidence: 99%
“…Maintaining timely information on road networks [2], especially in developing cities where road networks may change rapidly, is challenging. Conventional ground-based survey map updating techniques are restricted because of the long periods required to collect and organize geographic information [1]. Remote sensing interpretations can be used to extract road maps but cannot capture large-scale and complex road networks, and are affected by occlusions caused by clouds, mist and trees.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…In a major departure from prior work, we combine initial density processing as in [9,22,7,21] with subsequent trajectory processing [6,11,24,12,13,3,18]. As shown in [4], density processing holds a significant advantage over trajectory processing in terms of robustness to noise and computational complexity, both supremely important considerations as we grow the amount of trace data used.…”
Section: Topology Refinement ( §6)mentioning
confidence: 99%
“…In order to extract the road map, a second pass is made through these clusters, connecting with road segments those clusters that fall along the path of the raw GPS traces. Methods that belong to this class include algorithms described by Edelkamp and Schrödl [11], Schroedl et al [19], Worrall and Nebot [24], Guo et al [12], Jang et al [13], and Agamennoni et al [3].…”
Section: Related Workmentioning
confidence: 99%