A Blockchain-Enabled Distributed System for Trustworthy and Collaborative Intelligent Vehicle Re-Identification

被引:1
|
作者
Wang, Shuai [1 ,2 ]
Yang, Da [1 ,2 ]
Sheng, Hao [1 ,2 ]
Shen, Jiahao [1 ,2 ]
Zhang, Yang [3 ]
Ke, Wei [4 ]
机构
[1] Beihang Univ, Sch Comp Sci & Engn, State Key Lab Virtual Real Technol & Syst, State Key Lab Software Dev Enivorment, Beijing 100191, Peoples R China
[2] Beihang Univ, Zhongfa Aviat Inst, Key Lab Data Sci & Intelligent Comp, Hangzhou 311115, Zhejiang, Peoples R China
[3] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
[4] Macao Polytech Univ, Fac Appl Sci, Taipa 999078, Macao, Peoples R China
来源
基金
国家重点研发计划;
关键词
Intelligent vehicles; Blockchains; Cameras; Task analysis; Collaboration; Internet of Things; Feature extraction; Blockchain; collaborative computation; distributed system; intelligent vehicle; vehicle re-identification; NETWORK;
D O I
10.1109/TIV.2023.3347267
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:3271 / 3282
页数:12
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