Collective behavior recognition using compact descriptors Article Swipe
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1809.10499
This paper presents a novel hierarchical approach for collective behavior recognition based solely on ground-plane trajectories. In the first layer of our classifier, we introduce a novel feature called Personal Interaction Descriptor (PID), which combines the spatial distribution of a pair of pedestrians within a temporal window with a pyramidal representation of the relative speed to detect pairwise interactions. These interactions are then combined with higher level features related to the mean speed and shape formed by the pedestrians in the scene, generating a Collective Behavior Descriptor (CBD) that is used to identify collective behaviors in a second stage. In both layers, Random Forests were used as classifiers, since they allow features of different natures to be combined seamlessly. Our experimental results indicate that the proposed method achieves results on par with state of the art techniques with a better balance of class errors. Moreover, we show that our method can generalize well across different camera setups through cross-dataset experiments.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1809.10499
- https://arxiv.org/pdf/1809.10499
- OA Status
- green
- Cited By
- 2
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2894115607
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2894115607Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.1809.10499Digital Object Identifier
- Title
-
Collective behavior recognition using compact descriptorsWork title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2018Year of publication
- Publication date
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2018-09-27Full publication date if available
- Authors
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Gustavo Führ, Cláudio R. JungList of authors in order
- Landing page
-
https://arxiv.org/abs/1809.10499Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1809.10499Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/1809.10499Direct OA link when available
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Pairwise comparison, Computer science, Classifier (UML), Artificial intelligence, Pattern recognition (psychology), Random forest, Representation (politics), Feature (linguistics), Sliding window protocol, Window (computing), Politics, Law, Linguistics, Operating system, Political science, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
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2022: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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23Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
| sustainable_development_goals[0].score | 0.7200000286102295 |
| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile |