City-Scale Multi-Camera Vehicle Tracking of Vehicles based on YOLOv7

Duong Nguyen Ngoc Tran; Long Hoang Pham; Huy Hung Nguyen; Jae Wook Jeon

doi:10.1109/ICCE-Asia57006.2022.9954809

City-Scale Multi-Camera Vehicle Tracking of Vehicles based on YOLOv7

Duong Nguyen Ngoc Tran
, Long Hoang Pham
, Huy Hung Nguyen
, Jae Wook Jeon

Sungkyunkwan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

17 Scopus citations

Abstract

Multi-Target Multi-Camera Tracking has a massive Intelligent Traffic Surveillance System application domain. In this paper, we introduce the framework using YOLOv7, DeepSORT, and Re-ID to provide the identification of vehicles via a camera network. At first, we localize a vehicle in every single camera. Then, the Re-ID obtains the unique feature of each bounding box we crop from detection. We use DeepSORT and Trajectory Clustering from the list of features to keep the vehicle's identity from a single camera to a multi-camera. The experiment result shows the promise of the framework in the extensive system.

Original language	English
Title of host publication	2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665464345
DOIs	https://doi.org/10.1109/ICCE-Asia57006.2022.9954809
State	Published - 2022
Externally published	Yes
Event	2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022 - Yeosu, Korea, Republic of Duration: 26 Oct 2022 → 28 Oct 2022

Publication series

Name	2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022

Conference

Conference	2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022
Country/Territory	Korea, Republic of
City	Yeosu
Period	26/10/22 → 28/10/22

UN SDGs

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

SDG 11 Sustainable Cities and Communities

Keywords

multi-object tracking
object detection
re-identification
traffic surveillance system

Access to Document

10.1109/ICCE-Asia57006.2022.9954809

Cite this

Tran, D. N. N., Pham, L. H., Nguyen, H. H., & Jeon, J. W. (2022). City-Scale Multi-Camera Vehicle Tracking of Vehicles based on YOLOv7. In 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022 (2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-Asia57006.2022.9954809

@inproceedings{43ebca2756d04fc89d12b3fb6d33e34e,

title = "City-Scale Multi-Camera Vehicle Tracking of Vehicles based on YOLOv7",

abstract = "Multi-Target Multi-Camera Tracking has a massive Intelligent Traffic Surveillance System application domain. In this paper, we introduce the framework using YOLOv7, DeepSORT, and Re-ID to provide the identification of vehicles via a camera network. At first, we localize a vehicle in every single camera. Then, the Re-ID obtains the unique feature of each bounding box we crop from detection. We use DeepSORT and Trajectory Clustering from the list of features to keep the vehicle's identity from a single camera to a multi-camera. The experiment result shows the promise of the framework in the extensive system.",

keywords = "multi-object tracking, object detection, re-identification, traffic surveillance system",

author = "Tran, \{Duong Nguyen Ngoc\} and Pham, \{Long Hoang\} and Nguyen, \{Huy Hung\} and Jeon, \{Jae Wook\}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022 ; Conference date: 26-10-2022 Through 28-10-2022",

year = "2022",

doi = "10.1109/ICCE-Asia57006.2022.9954809",

language = "English",

series = "2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022",

}

Tran, DNN, Pham, LH, Nguyen, HH & Jeon, JW 2022, City-Scale Multi-Camera Vehicle Tracking of Vehicles based on YOLOv7. in 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022. 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022, Institute of Electrical and Electronics Engineers Inc., 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022, Yeosu, Korea, Republic of, 26/10/22. https://doi.org/10.1109/ICCE-Asia57006.2022.9954809

City-Scale Multi-Camera Vehicle Tracking of Vehicles based on YOLOv7. / Tran, Duong Nguyen Ngoc; Pham, Long Hoang; Nguyen, Huy Hung et al.
2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - City-Scale Multi-Camera Vehicle Tracking of Vehicles based on YOLOv7

AU - Tran, Duong Nguyen Ngoc

AU - Pham, Long Hoang

AU - Nguyen, Huy Hung

AU - Jeon, Jae Wook

PY - 2022

Y1 - 2022

N2 - Multi-Target Multi-Camera Tracking has a massive Intelligent Traffic Surveillance System application domain. In this paper, we introduce the framework using YOLOv7, DeepSORT, and Re-ID to provide the identification of vehicles via a camera network. At first, we localize a vehicle in every single camera. Then, the Re-ID obtains the unique feature of each bounding box we crop from detection. We use DeepSORT and Trajectory Clustering from the list of features to keep the vehicle's identity from a single camera to a multi-camera. The experiment result shows the promise of the framework in the extensive system.

AB - Multi-Target Multi-Camera Tracking has a massive Intelligent Traffic Surveillance System application domain. In this paper, we introduce the framework using YOLOv7, DeepSORT, and Re-ID to provide the identification of vehicles via a camera network. At first, we localize a vehicle in every single camera. Then, the Re-ID obtains the unique feature of each bounding box we crop from detection. We use DeepSORT and Trajectory Clustering from the list of features to keep the vehicle's identity from a single camera to a multi-camera. The experiment result shows the promise of the framework in the extensive system.

KW - multi-object tracking

KW - object detection

KW - re-identification

KW - traffic surveillance system

UR - https://www.scopus.com/pages/publications/85143818123

U2 - 10.1109/ICCE-Asia57006.2022.9954809

DO - 10.1109/ICCE-Asia57006.2022.9954809

M3 - Conference contribution

AN - SCOPUS:85143818123

T3 - 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022

BT - 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022

Y2 - 26 October 2022 through 28 October 2022

ER -

Tran DNN, Pham LH, Nguyen HH, Jeon JW. City-Scale Multi-Camera Vehicle Tracking of Vehicles based on YOLOv7. In 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022). doi: 10.1109/ICCE-Asia57006.2022.9954809

City-Scale Multi-Camera Vehicle Tracking of Vehicles based on YOLOv7

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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