Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs

Yichang Liu; Mark Reynolds; Du Huynh; Ghulam Mubashar Hassan

doi:10.1109/ICAIIS49377.2020.9194930

Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs

Yichang Liu, Mark Reynolds, Du Huynh, Ghulam Mubashar Hassan

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

2 Citations (Scopus)

Abstract

With the development of AIoT, Smart City Traffic Management System based on artificial intelligence and big data has gradually become an effective urban management system. Instead of raw data from sensors and cameras, some specific information, such as the length of vehicles are more expected to be gained in Smart City. In this paper, a vehicle length estimation method is proposed based on the Convolutional Neural Networks (CNN) and image processing. The vehicles will be detected by YOLOs, a CNN model for object detection. Then the approximate length of vehicles will be estimated. Experiment results verify that the vehicle length estimation based on YOLOs approach a high accuracy at low time consumption.

Original language	English
Title of host publication	Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)
Editors	Xia Huang
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	118-121
Number of pages	4
ISBN (Electronic)	9781728165905
ISBN (Print)	978‐1‐7281‐6590‐5
DOIs	https://doi.org/10.1109/ICAIIS49377.2020.9194930
Publication status	Published - 22 Mar 2020
Event	IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) - Dailan, China Duration: 20 Mar 2020 → 22 Mar 2020

Publication series

Name	IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS

Conference

Conference	IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)
Abbreviated title	ICAIIS
Country/Territory	China
City	Dailan
Period	20/03/20 → 22/03/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICAIIS49377.2020.9194930

Cite this

Liu, Y., Reynolds, M., Huynh, D., & Hassan, G. M. (2020). Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs. In X. Huang (Ed.), Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS) (pp. 118-121). Article 9194930 (IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICAIIS49377.2020.9194930

Liu, Yichang ; Reynolds, Mark ; Huynh, Du et al. / Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs. Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS). editor / Xia Huang. IEEE, Institute of Electrical and Electronics Engineers, 2020. pp. 118-121 (IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS).

@inproceedings{0e702cf450b049a1a3f6b378a488bcf0,

title = "Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs",

abstract = "With the development of AIoT, Smart City Traffic Management System based on artificial intelligence and big data has gradually become an effective urban management system. Instead of raw data from sensors and cameras, some specific information, such as the length of vehicles are more expected to be gained in Smart City. In this paper, a vehicle length estimation method is proposed based on the Convolutional Neural Networks (CNN) and image processing. The vehicles will be detected by YOLOs, a CNN model for object detection. Then the approximate length of vehicles will be estimated. Experiment results verify that the vehicle length estimation based on YOLOs approach a high accuracy at low time consumption.",

author = "Yichang Liu and Mark Reynolds and Du Huynh and Hassan, {Ghulam Mubashar}",

year = "2020",

month = mar,

day = "22",

doi = "10.1109/ICAIIS49377.2020.9194930",

language = "English",

isbn = "978‐1‐7281‐6590‐5",

series = "IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

pages = "118--121",

editor = "Huang, {Xia }",

booktitle = "Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)",

address = "United States",

note = "IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS), ICAIIS ; Conference date: 20-03-2020 Through 22-03-2020",

}

Liu, Y, Reynolds, M , Huynh, D & Hassan, GM 2020, Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs. in X Huang (ed.), Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)., 9194930, IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS, IEEE, Institute of Electrical and Electronics Engineers, pp. 118-121, IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS), Dailan, China, 20/03/20. https://doi.org/10.1109/ICAIIS49377.2020.9194930

Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs. / Liu, Yichang; Reynolds, Mark ; Huynh, Du et al.
Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS). ed. / Xia Huang. IEEE, Institute of Electrical and Electronics Engineers, 2020. p. 118-121 9194930 (IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS).

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

TY - GEN

T1 - Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs

AU - Liu, Yichang

AU - Reynolds, Mark

AU - Huynh, Du

AU - Hassan, Ghulam Mubashar

PY - 2020/3/22

Y1 - 2020/3/22

N2 - With the development of AIoT, Smart City Traffic Management System based on artificial intelligence and big data has gradually become an effective urban management system. Instead of raw data from sensors and cameras, some specific information, such as the length of vehicles are more expected to be gained in Smart City. In this paper, a vehicle length estimation method is proposed based on the Convolutional Neural Networks (CNN) and image processing. The vehicles will be detected by YOLOs, a CNN model for object detection. Then the approximate length of vehicles will be estimated. Experiment results verify that the vehicle length estimation based on YOLOs approach a high accuracy at low time consumption.

AB - With the development of AIoT, Smart City Traffic Management System based on artificial intelligence and big data has gradually become an effective urban management system. Instead of raw data from sensors and cameras, some specific information, such as the length of vehicles are more expected to be gained in Smart City. In this paper, a vehicle length estimation method is proposed based on the Convolutional Neural Networks (CNN) and image processing. The vehicles will be detected by YOLOs, a CNN model for object detection. Then the approximate length of vehicles will be estimated. Experiment results verify that the vehicle length estimation based on YOLOs approach a high accuracy at low time consumption.

UR - http://www.scopus.com/inward/record.url?scp=85095607468&partnerID=8YFLogxK

U2 - 10.1109/ICAIIS49377.2020.9194930

DO - 10.1109/ICAIIS49377.2020.9194930

M3 - Conference paper

SN - 978‐1‐7281‐6590‐5

T3 - IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS

SP - 118

EP - 121

BT - Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)

A2 - Huang, Xia

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)

Y2 - 20 March 2020 through 22 March 2020

ER -

Liu Y, Reynolds M , Huynh D , Hassan GM. Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs. In Huang X, editor, Proceedings of 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS). IEEE, Institute of Electrical and Electronics Engineers. 2020. p. 118-121. 9194930. (IEEE International Conference on Artificial Intelligence and Information Systems, ICAIIS). doi: 10.1109/ICAIIS49377.2020.9194930

Study of Accurate and Fast Estimation Method of Vehicle Length Based on YOLOs

Abstract

Publication series

Conference

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this