Smart City Gnosys

Smart city article details

Title	Synthehicle: Multi-Vehicle Multi-Camera Tracking In Virtual Cities
ID_Doc	54231
Authors	Herzog F.; Chen J.; Teepe T.; Gilg J.; Hormann S.; Rigoll G.
Year	2023
Published	Proceedings - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023
DOI	http://dx.doi.org/10.1109/WACVW58289.2023.00005
Abstract	Smart City applications such as intelligent traffic routing, accident prevention or vehicle surveillance rely on computer vision methods for exact vehicle localization and tracking. Privacy issues make collecting real data difficult, and labeling data is a time-consuming and costly process. Due to the scarcity of accurately labeled data, detecting and tracking vehicles in 3D from multiple cameras proves challenging to explore. We present a massive synthetic dataset for multiple vehicle tracking and segmentation in multiple overlapping and non-overlapping camera views. Unlike existing datasets, which only provide tracking ground truth for 2D bounding boxes, our dataset additionally contains perfect labels for 3D bounding boxes in camera- and world coordinates, depth estimation, and instance, semantic and panoptic segmentation. The dataset consists of 17 hours of labeled video material, recorded from 340 cameras in 64 diverse day, rain, dawn, and night scenes, making it the most extensive dataset for multi-target multi-camera tracking so far. We provide baselines for detection, vehicle re-identification, and single- and multi-camera tracking. Code and data are publicly available. 11Code and data: https://github.com/fubel/synthehicle © 2023 IEEE.
Author Keywords

Similar Articles

Id	Similarity	Authors	Title	Published
38146	0.873	Li Y.-L.; Chin Z.-Y.; Chang M.-C.; Chiang C.-K.	Multi-Camera Tracking By Candidate Intersection Ratio Tracklet Matching	IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (2021)
6290	0.87	Nguyen X.-D.; Vu A.-K.N.; Nguyen T.-D.; Phan N.; Dinh B.-D.D.; Nguyen N.-D.; Nguyen T.V.; Nguyen V.-T.; Le D.-D.	Adaptive Multi-Vehicle Motion Counting	Signal, Image and Video Processing, 16, 8 (2022)
17814	0.868	Wang X.; Sun Z.; Chehri A.; Jeon G.; Song Y.	Deep Learning And Multi-Modal Fusion For Real-Time Multi-Object Tracking: Algorithms, Challenges, Datasets, And Comparative Study	Information Fusion, 105 (2024)
58684	0.859	Hsu H.-M.; Wang Y.; Hwang J.-N.	Traffic-Aware Multi-Camera Tracking Of Vehicles Based On Reid And Camera Link Model	MM 2020 - Proceedings of the 28th ACM International Conference on Multimedia (2020)
5878	0.858	Lin Y.; Lockyer S.; Evans A.; Zarbock M.; Zhang N.	Ablation Study For Multi-Camera Vehicle Tracking Using Cityflow Dataset	Proceedings of SPIE - The International Society for Optical Engineering, 13517 (2025)
38291	0.858	Patil K.; Gatagat D.; Rumane O.; Pashankar S.; chumchu P.	Multi-Object Urban Dataset: A Resource For Detecting Pedestrians, Traffic And Motorbikes	Data in Brief, 57 (2024)
53206	0.856	Piadyk Y.; Rulff J.; Brewer E.; Hosseini M.; Ozbay K.; Sankaradas M.; Chakradhar S.; Silva C.	Streetaware: A High-Resolution Synchronized Multimodal Urban Scene Dataset	Sensors, 23, 7 (2023)
61474	0.854	Dong Z.; Lu Y.; Tong G.; Shu Y.; Wang S.; Shi W.	Watchdog: Real-Time Vehicle Tracking On Geo-Distributed Edge Nodes	ACM Transactions on Internet of Things, 4, 1 (2023)
16613	0.854	Li B.; Qin K.; Cui Z.; Xu Q.; Xu Z.	Cross-Camera Vehicle Trajectory Estimation Towards Traffic Flow	2022 International Conference on Image Processing, Computer Vision and Machine Learning, ICICML 2022 (2022)
14210	0.854	Wei P.; Shi H.; Yang J.; Qian J.; Ji Y.; Jiang X.	City-Scale Vehicle Tracking And Traffic Flow Estimation Using Low Frame-Rate Traffic Cameras	UbiComp/ISWC 2019- - Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers (2019)