TY - JOUR
T1 - A Blockchain-Enabled Distributed System for Trustworthy and Collaborative Intelligent Vehicle Re-Identification
AU - Wang, Shuai
AU - Yang, Da
AU - Sheng, Hao
AU - Shen, Jiahao
AU - Zhang, Yang
AU - Ke, Wei
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2024/2/1
Y1 - 2024/2/1
N2 - Vehicle re-identification (ReID) is a hot topic in intelligent city surveillance. With the development of smart cameras and vehicular edge computing (VEC), numerous media data has opened up new possibilities for enhancing the applications of vehicle ReID. However, traditional vehicle re-identification systems face the following challenges: 1) it is difficult to recognize the identities of the vehicles in various views and similar appearance, 2) the current system is hard to be extended to large-scale of cameras in a low-trust VEC environment. To solve these problems, we propose a Blockchain-based Collaborative Vehicle ReID (BCV-ReID) system in this paper. It contains two core parts including Viewpoint-identity Query Net (VQNet) and VehicleChain (VChain). By utilizing the viewpoint information and local details simultaneously, VQNet can distinguish the vehicle identities in various cross-camera scenes. It employs viewpoint queries and spatial self-attention to learn the inherent correlation of the vehicle parts, enhancing the ability to distinguish vehicles among various viewpoints. Then, we integrate VChain with VQNet to realize a collaborative vehicle ReID system. The ReID task is illustrated from the perspective of blockchain transactions. All transactions are validated by a deeply integrated ReID consensus to counter potential malicious attacks. Experiments show that the proposed method achieves comparable results in three famous ReID datasets, as well as outstanding performance in real applications.
AB - Vehicle re-identification (ReID) is a hot topic in intelligent city surveillance. With the development of smart cameras and vehicular edge computing (VEC), numerous media data has opened up new possibilities for enhancing the applications of vehicle ReID. However, traditional vehicle re-identification systems face the following challenges: 1) it is difficult to recognize the identities of the vehicles in various views and similar appearance, 2) the current system is hard to be extended to large-scale of cameras in a low-trust VEC environment. To solve these problems, we propose a Blockchain-based Collaborative Vehicle ReID (BCV-ReID) system in this paper. It contains two core parts including Viewpoint-identity Query Net (VQNet) and VehicleChain (VChain). By utilizing the viewpoint information and local details simultaneously, VQNet can distinguish the vehicle identities in various cross-camera scenes. It employs viewpoint queries and spatial self-attention to learn the inherent correlation of the vehicle parts, enhancing the ability to distinguish vehicles among various viewpoints. Then, we integrate VChain with VQNet to realize a collaborative vehicle ReID system. The ReID task is illustrated from the perspective of blockchain transactions. All transactions are validated by a deeply integrated ReID consensus to counter potential malicious attacks. Experiments show that the proposed method achieves comparable results in three famous ReID datasets, as well as outstanding performance in real applications.
KW - Blockchain
KW - collaborative computation
KW - distributed system
KW - intelligent vehicle
KW - vehicle re-identification
UR - http://www.scopus.com/inward/record.url?scp=85181568115&partnerID=8YFLogxK
U2 - 10.1109/TIV.2023.3347267
DO - 10.1109/TIV.2023.3347267
M3 - Article
AN - SCOPUS:85181568115
SN - 2379-8858
VL - 9
SP - 3271
EP - 3282
JO - IEEE Transactions on Intelligent Vehicles
JF - IEEE Transactions on Intelligent Vehicles
IS - 2
ER -