Robust Edge-Direct Visual Odometry based on CNN edge detection and Shi-Tomasi corner optimization Article Swipe
Kengdong Lu
,
Jintao Cheng
,
Yubin Zhou
,
Juncan Deng
,
Rui Fan
,
Kaiqing Luo
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2110.11064
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2110.11064
In this paper, we propose a robust edge-direct visual odometry (VO) based on CNN edge detection and Shi-Tomasi corner optimization. Four layers of pyramids were extracted from the image in the proposed method to reduce the motion error between frames. This solution used CNN edge detection and Shi-Tomasi corner optimization to extract information from the image. Then, the pose estimation is performed using the Levenberg-Marquardt (LM) algorithm and updating the keyframes. Our method was compared with the dense direct method, the improved direct method of Canny edge detection, and ORB-SLAM2 system on the RGB-D TUM benchmark. The experimental results indicate that our method achieves better robustness and accuracy.
Related Topics
Concepts
Artificial intelligence
Visual odometry
Robustness (evolution)
Computer vision
Canny edge detector
Computer science
Edge detection
Enhanced Data Rates for GSM Evolution
Corner detection
Benchmark (surveying)
Image gradient
RGB color model
Image (mathematics)
Image processing
Robot
Chemistry
Biochemistry
Geodesy
Geography
Gene
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2110.11064
- https://arxiv.org/pdf/2110.11064
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4286897963
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4286897963Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2110.11064Digital Object Identifier
- Title
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Robust Edge-Direct Visual Odometry based on CNN edge detection and Shi-Tomasi corner optimizationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-10-21Full publication date if available
- Authors
-
Kengdong Lu, Jintao Cheng, Yubin Zhou, Juncan Deng, Rui Fan, Kaiqing LuoList of authors in order
- Landing page
-
https://arxiv.org/abs/2110.11064Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2110.11064Direct 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/2110.11064Direct OA link when available
- Concepts
-
Artificial intelligence, Visual odometry, Robustness (evolution), Computer vision, Canny edge detector, Computer science, Edge detection, Enhanced Data Rates for GSM Evolution, Corner detection, Benchmark (surveying), Image gradient, RGB color model, Image (mathematics), Image processing, Robot, Chemistry, Biochemistry, Geodesy, Geography, GeneTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.improved | 81 |
| abstract_inverted_index.indicate | 99 |
| abstract_inverted_index.odometry | 9 |
| abstract_inverted_index.proposed | 31 |
| abstract_inverted_index.pyramids | 23 |
| abstract_inverted_index.solution | 41 |
| abstract_inverted_index.updating | 68 |
| abstract_inverted_index.ORB-SLAM2 | 89 |
| abstract_inverted_index.accuracy. | 107 |
| abstract_inverted_index.algorithm | 66 |
| abstract_inverted_index.detection | 15, 45 |
| abstract_inverted_index.extracted | 25 |
| abstract_inverted_index.performed | 61 |
| abstract_inverted_index.Shi-Tomasi | 17, 47 |
| abstract_inverted_index.benchmark. | 95 |
| abstract_inverted_index.detection, | 87 |
| abstract_inverted_index.estimation | 59 |
| abstract_inverted_index.keyframes. | 70 |
| abstract_inverted_index.robustness | 105 |
| abstract_inverted_index.edge-direct | 7 |
| abstract_inverted_index.information | 52 |
| abstract_inverted_index.experimental | 97 |
| abstract_inverted_index.optimization | 49 |
| abstract_inverted_index.optimization. | 19 |
| abstract_inverted_index.Levenberg-Marquardt | 64 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile |