TrackletMapper: Ground Surface Segmentation and Mapping from Traffic Participant Trajectories Article Swipe
Jannik Zürn
,
S. M. Weber
,
Wolfram Burgard
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2209.05247
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2209.05247
Robustly classifying ground infrastructure such as roads and street crossings is an essential task for mobile robots operating alongside pedestrians. While many semantic segmentation datasets are available for autonomous vehicles, models trained on such datasets exhibit a large domain gap when deployed on robots operating in pedestrian spaces. Manually annotating images recorded from pedestrian viewpoints is both expensive and time-consuming. To overcome this challenge, we propose TrackletMapper, a framework for annotating ground surface types such as sidewalks, roads, and street crossings from object tracklets without requiring human-annotated data. To this end, we project the robot ego-trajectory and the paths of other traffic participants into the ego-view camera images, creating sparse semantic annotations for multiple types of ground surfaces from which a ground segmentation model can be trained. We further show that the model can be self-distilled for additional performance benefits by aggregating a ground surface map and projecting it into the camera images, creating a denser set of training annotations compared to the sparse tracklet annotations. We qualitatively and quantitatively attest our findings on a novel large-scale dataset for mobile robots operating in pedestrian areas. Code and dataset will be made available at http://trackletmapper.cs.uni-freiburg.de.
Related Topics
Concepts
Computer science
Segmentation
Artificial intelligence
Pedestrian
Robot
Set (abstract data type)
Task (project management)
Computer vision
Trajectory
Ground truth
Domain (mathematical analysis)
Geography
Economics
Management
Mathematics
Astronomy
Mathematical analysis
Programming language
Archaeology
Physics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2209.05247
- https://arxiv.org/pdf/2209.05247
- OA Status
- green
- Cited By
- 4
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4295680081
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4295680081Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2209.05247Digital Object Identifier
- Title
-
TrackletMapper: Ground Surface Segmentation and Mapping from Traffic Participant TrajectoriesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-09-12Full publication date if available
- Authors
-
Jannik Zürn, S. M. Weber, Wolfram BurgardList of authors in order
- Landing page
-
https://arxiv.org/abs/2209.05247Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2209.05247Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2209.05247Direct OA link when available
- Concepts
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Computer science, Segmentation, Artificial intelligence, Pedestrian, Robot, Set (abstract data type), Task (project management), Computer vision, Trajectory, Ground truth, Domain (mathematical analysis), Geography, Economics, Management, Mathematics, Astronomy, Mathematical analysis, Programming language, Archaeology, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2023: 2Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.compared | 160 |
| abstract_inverted_index.creating | 108, 153 |
| abstract_inverted_index.datasets | 24, 34 |
| abstract_inverted_index.deployed | 41 |
| abstract_inverted_index.ego-view | 105 |
| abstract_inverted_index.findings | 172 |
| abstract_inverted_index.multiple | 113 |
| abstract_inverted_index.overcome | 61 |
| abstract_inverted_index.recorded | 51 |
| abstract_inverted_index.semantic | 22, 110 |
| abstract_inverted_index.surfaces | 117 |
| abstract_inverted_index.tracklet | 164 |
| abstract_inverted_index.trained. | 126 |
| abstract_inverted_index.training | 158 |
| abstract_inverted_index.alongside | 18 |
| abstract_inverted_index.available | 26, 191 |
| abstract_inverted_index.crossings | 9, 80 |
| abstract_inverted_index.essential | 12 |
| abstract_inverted_index.expensive | 57 |
| abstract_inverted_index.framework | 68 |
| abstract_inverted_index.operating | 17, 44, 181 |
| abstract_inverted_index.requiring | 85 |
| abstract_inverted_index.tracklets | 83 |
| abstract_inverted_index.vehicles, | 29 |
| abstract_inverted_index.additional | 137 |
| abstract_inverted_index.annotating | 49, 70 |
| abstract_inverted_index.autonomous | 28 |
| abstract_inverted_index.challenge, | 63 |
| abstract_inverted_index.pedestrian | 46, 53, 183 |
| abstract_inverted_index.projecting | 147 |
| abstract_inverted_index.sidewalks, | 76 |
| abstract_inverted_index.viewpoints | 54 |
| abstract_inverted_index.aggregating | 141 |
| abstract_inverted_index.annotations | 111, 159 |
| abstract_inverted_index.classifying | 1 |
| abstract_inverted_index.large-scale | 176 |
| abstract_inverted_index.performance | 138 |
| abstract_inverted_index.annotations. | 165 |
| abstract_inverted_index.participants | 102 |
| abstract_inverted_index.pedestrians. | 19 |
| abstract_inverted_index.segmentation | 23, 122 |
| abstract_inverted_index.qualitatively | 167 |
| abstract_inverted_index.ego-trajectory | 95 |
| abstract_inverted_index.infrastructure | 3 |
| abstract_inverted_index.quantitatively | 169 |
| abstract_inverted_index.self-distilled | 135 |
| abstract_inverted_index.TrackletMapper, | 66 |
| abstract_inverted_index.human-annotated | 86 |
| abstract_inverted_index.time-consuming. | 59 |
| abstract_inverted_index.http://trackletmapper.cs.uni-freiburg.de. | 193 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.5099999904632568 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile |