A Novel Method for Road Anomaly Objects Detection in the Traffic Environment With Multi-Mechanism Fusion Article Swipe
Wenyan Ci
,
Jiayin Xuan
,
Runze Lin
,
Shan Lu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/access.2024.3359695
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/access.2024.3359695
In the modern automotive industry, Advanced Driving Assistance Systems (ADAS) have gradually become a standard feature in various types of vehicles, with the important function of detecting road anomalies. The appearance of anomalies on the road can be attributed to unexpected situations while driving, and the current methods for detecting distant or small anomalies are not highly accurate. Therefore, in this paper, a method is proposed that uses semantic segmentation to extract key features from the image, and obtaining a new synthesized image by image resynthesis. Then, segmentation uncertainty and depth information are used to compare the differences between multiple feature maps and the input image to highlight the anomalies. Additionally, a postprocessor is designed to use an anomaly score to enhance the recognition of anomaly target and reduce false positives caused by noise. Experiments are conducted on the Obstacle Track dataset and the Lost and Found dataset, and various methods for detecting anomaly objects are compared. The experimental results demonstrate that the method proposed in this paper can effectively detect un-common objects in the training dataset in road anomaly object detection. It improves the detection rate and reduces the false positive rate based on previous anomaly detection methods. The proposed method presented in this paper achieves high detection rates for both seen and unseen anomaly objects in the training set, which enhances the generalization ability of anomaly detection in the road area of interest.
Related Topics
Concepts
Anomaly detection
Computer science
Artificial intelligence
False positive paradox
Pattern recognition (psychology)
Anomaly (physics)
Feature (linguistics)
Segmentation
Object detection
Computer vision
Image (mathematics)
Image segmentation
Generalization
Data mining
Mathematics
Philosophy
Mathematical analysis
Physics
Condensed matter physics
Linguistics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2024.3359695
- https://ieeexplore.ieee.org/ielx7/6287639/6514899/10443367.pdf
- OA Status
- gold
- Cited By
- 2
- References
- 46
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392007359
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4392007359Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/access.2024.3359695Digital Object Identifier
- Title
-
A Novel Method for Road Anomaly Objects Detection in the Traffic Environment With Multi-Mechanism FusionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-01Full publication date if available
- Authors
-
Wenyan Ci, Jiayin Xuan, Runze Lin, Shan LuList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2024.3359695Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/6287639/6514899/10443367.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/6287639/6514899/10443367.pdfDirect OA link when available
- Concepts
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Anomaly detection, Computer science, Artificial intelligence, False positive paradox, Pattern recognition (psychology), Anomaly (physics), Feature (linguistics), Segmentation, Object detection, Computer vision, Image (mathematics), Image segmentation, Generalization, Data mining, Mathematics, Philosophy, Mathematical analysis, Physics, Condensed matter physics, LinguisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2Per-year citation counts (last 5 years)
- References (count)
-
46Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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