ScatterHough: Automatic Lane Detection from Noisy LiDAR Data
Abstract
:1. Introduction
- neighbor voting method is introduced into HT to allow points in the neighborhood of estimated value to vote, tailed for scatter points;
- neighbor vote-reduction method is introduced into HT to drop votes that already contribute to existing fitted lines for better curve fitting;
- Experimental results on the popular PandaSet demonstrate that our method achieves better performance compared with other line fitting approaches.
2. Related Work
3. The Proposed ScatterHough
3.1. Neighbor Voting
Algorithm 1: Neighbor Voting. |
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3.2. Neighbor Vote-Reduction
Algorithm 2: Neighbor Vote-reduction. |
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4. Evaluation
4.1. Dataset
4.2. Experimental Results
4.3. Computational Efficiency
4.4. Hyper-Parameters Setting
4.5. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Scene | Method | Metric | Result |
---|---|---|---|
Straight dual-lane line | ScatterHough (Ours) | inline | 665 |
total | 821 | ||
accuracy | 0.8090 | ||
Ransac | inline | 533 | |
total | 821 | ||
accuracy | 0.6492 | ||
Dsac | inline | 280 | |
total | 821 | ||
accuracy | 0.3410 | ||
multiRansac | inline | 614 | |
total | 821 | ||
accuracy | 0.7479 | ||
Poly | inline | 216 | |
total | 821 | ||
accuracy | 0.2631 | ||
3-lane crossroad | ScatterHough (Ours) | inline | 335 |
total | 479 | ||
accuracy | 0.6994 | ||
Ransac | inline | 179 | |
total | 479 | ||
accuracy | 0.3737 | ||
Dsac | inline | 12 | |
total | 479 | ||
accuracy | 0.0251 | ||
multiRansac | inline | 31 | |
total | 479 | ||
accuracy | 0.0647 | ||
Poly | inline | 5 | |
total | 479 | ||
accuracy | 0.0104 | ||
fork road | ScatterHough (Ours) | inline | 90 |
total | 178 | ||
accuracy | 0.5056 | ||
Ransac | inline | 50 | |
total | 178 | ||
accuracy | 0.2809 | ||
Dsac | inline | 3 | |
total | 178 | ||
accuracy | 0.0169 | ||
multiRansac | inline | 41 | |
total | 178 | ||
accuracy | 0.2303 | ||
Poly | inline | 0 | |
total | 178 | ||
accuracy | 0 | ||
slope road | ScatterHough (Ours) | inline | 594 |
total | 734 | ||
accuracy | 0.8093 | ||
Ransac | inline | 55 | |
total | 734 | ||
accuracy | 0.0749 | ||
Dsac | inline | 125 | |
total | 734 | ||
accuracy | 0.1703 | ||
multiRansac | inline | 162 | |
total | 734 | ||
accuracy | 0.2207 | ||
Poly | inline | 52 | |
total | 734 | ||
accuracy | 0.0708 |
Scene | Method | Metric | Result |
---|---|---|---|
double dashed line | ScatterHough (Ours) | inline | 393 |
total | 429 | ||
accuracy | 0.9161 | ||
Ransac | inline | 106 | |
total | 429 | ||
accuracy | 0.2471 | ||
Dsac | inline | 13 | |
total | 429 | ||
accuracy | 0.0303 | ||
multiRansac | inline | 305 | |
total | 429 | ||
accuracy | 0.7110 | ||
Poly | inline | 0 | |
total | 429 | ||
accuracy | 0 | ||
curve line | ScatterHough (Ours) | inline | 794 |
total | 1335 | ||
accuracy | 0.5947 | ||
Ransac | inline | 688 | |
total | 1335 | ||
accuracy | 0.5154 | ||
Dsac | inline | 44 | |
total | 1335 | ||
accuracy | 0.0330 | ||
multiRansac | inline | 425 | |
total | 1335 | ||
accuracy | 0.3184 | ||
Poly | inline | 23 | |
total | 1335 | ||
accuracy | 0.0172 | ||
Overall | ScatterHough (Ours) | inline | 3926 |
total | 5702 | ||
accuracy | 0.6885 | ||
Ransac | inline | 1983 | |
total | 5702 | ||
accuracy | 0.3477 | ||
Dsac | inline | 854 | |
total | 5702 | ||
accuracy | 0.1497 | ||
multiRansac | inline | 2124 | |
total | 5702 | ||
accuracy | 0.3725 | ||
Poly | inline | 356 | |
total | 5702 | ||
accuracy | 0.0624 |
Method | ScatterHough (Ours) | Ransac | Dsac | multiRansac | Poly |
---|---|---|---|---|---|
frames per second (FPS) | 12 | 8 | 2 | 5 | 313 |
d = 0.1 | d = 0.25 | d = 1 | d = 2 | |
---|---|---|---|---|
inline | 769 | 802 | 129 | 32 |
total | 821 | 821 | 821 | 821 |
accuracy | 0.9367 | 0.9769 | 0.1571 | 0.0390 |
= 10 | = 30 | = 60 | = 120 | |
---|---|---|---|---|
inline | 403 | 409 | 73 | 12 |
total | 429 | 429 | 429 | 429 |
accuracy | 0.9394 | 0.9534 | 0.1702 | 0.0280 |
= 5 | = 10 | = 15 | = 25 | |
---|---|---|---|---|
inline | 344 | 409 | 412 | 412 |
total | 429 | 429 | 429 | 429 |
accuracy | 0.8019 | 0.9534 | 0.9604 | 0.9604 |
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Zeng, H.; Jiang, S.; Cui, T.; Lu, Z.; Li, J.; Lee, B.-G.; Zhu, J.; Yang, X. ScatterHough: Automatic Lane Detection from Noisy LiDAR Data. Sensors 2022, 22, 5424. https://doi.org/10.3390/s22145424
Zeng H, Jiang S, Cui T, Lu Z, Li J, Lee B-G, Zhu J, Yang X. ScatterHough: Automatic Lane Detection from Noisy LiDAR Data. Sensors. 2022; 22(14):5424. https://doi.org/10.3390/s22145424
Chicago/Turabian StyleZeng, Honghao, Shihong Jiang, Tianxiang Cui, Zheng Lu, Jiawei Li, Boon-Giin Lee, Junsong Zhu, and Xiaoying Yang. 2022. "ScatterHough: Automatic Lane Detection from Noisy LiDAR Data" Sensors 22, no. 14: 5424. https://doi.org/10.3390/s22145424
APA StyleZeng, H., Jiang, S., Cui, T., Lu, Z., Li, J., Lee, B.-G., Zhu, J., & Yang, X. (2022). ScatterHough: Automatic Lane Detection from Noisy LiDAR Data. Sensors, 22(14), 5424. https://doi.org/10.3390/s22145424