Combining ROI-base and Superpixel Segmentation for Pedestrian Detection Article Swipe
Ji Ma
,
Jingjiao Li
,
Zhenni Li
,
Li Ma
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.2991/mmebc-16.2016.139
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.2991/mmebc-16.2016.139
Pedestrian Detection is a hot topic in recent years, which is attracting a large number of scholars.The detection models are developing from simple models to complex models and the detection accuracy has been greatly improved.DPM (deformable part model) become the best pedestrian detection model and also attracted many scholars to modify it.The biggest problem caused by complex models is low detection efficiency for the real-time application with the sliding windows framework.Meanwhile, the latent SVM algorithm in DPM mining parts information is greatly affected by the initialization of parts, and there is no exact solution.Aiming at the drawbacks of DPM, using the research achievement of salient object detection an background detection, we propose a novel pedestrian detection framework based on ROI and superpixel segmentation.Contrasting with DPM in experiments, our method have greatly improved in accuracy and efficiency.The proposed framework has the same reference to other complex models.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.2991/mmebc-16.2016.139
- https://download.atlantis-press.com/article/25858703.pdf
- OA Status
- gold
- References
- 17
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2522032739
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2522032739Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.2991/mmebc-16.2016.139Digital Object Identifier
- Title
-
Combining ROI-base and Superpixel Segmentation for Pedestrian DetectionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-01-01Full publication date if available
- Authors
-
Ji Ma, Jingjiao Li, Zhenni Li, Li MaList of authors in order
- Landing page
-
https://doi.org/10.2991/mmebc-16.2016.139Publisher landing page
- PDF URL
-
https://download.atlantis-press.com/article/25858703.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://download.atlantis-press.com/article/25858703.pdfDirect OA link when available
- Concepts
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Pedestrian detection, Artificial intelligence, Pedestrian, Computer science, Computer vision, Segmentation, Base (topology), Image segmentation, Region of interest, Pattern recognition (psychology), Mathematics, Engineering, Transport engineering, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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17Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.drawbacks | 96 |
| abstract_inverted_index.framework | 116, 137 |
| abstract_inverted_index.real-time | 64 |
| abstract_inverted_index.reference | 141 |
| abstract_inverted_index.Pedestrian | 0 |
| abstract_inverted_index.attracting | 11 |
| abstract_inverted_index.background | 108 |
| abstract_inverted_index.detection, | 109 |
| abstract_inverted_index.developing | 20 |
| abstract_inverted_index.efficiency | 61 |
| abstract_inverted_index.pedestrian | 41, 114 |
| abstract_inverted_index.superpixel | 121 |
| abstract_inverted_index.(deformable | 35 |
| abstract_inverted_index.achievement | 102 |
| abstract_inverted_index.application | 65 |
| abstract_inverted_index.information | 79 |
| abstract_inverted_index.experiments, | 126 |
| abstract_inverted_index.improved.DPM | 34 |
| abstract_inverted_index.scholars.The | 16 |
| abstract_inverted_index.efficiency.The | 135 |
| abstract_inverted_index.initialization | 85 |
| abstract_inverted_index.solution.Aiming | 93 |
| abstract_inverted_index.framework.Meanwhile, | 70 |
| abstract_inverted_index.segmentation.Contrasting | 122 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.5199999809265137 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.08442967 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |