A review of vision-based traffic semantic understanding in ITSs
J Chen, Q Wang, HH Cheng, W Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …
situations and emergencies more accurately and provide a more accurate basis for anomaly …
The 7th ai city challenge
Abstract The AI City Challenge's seventh edition emphasizes two domains at the intersection
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …
Vabus: Edge-cloud real-time video analytics via background understanding and subtraction
Edge-cloud collaborative video analytics is transforming the way data is being handled,
processed, and transmitted from the ever-growing number of surveillance cameras around …
processed, and transmitted from the ever-growing number of surveillance cameras around …
Reidtrack: Reid-only multi-target multi-camera tracking
Multi-target multi-camera tracking of persons in indoor scenarios such as retail stores or
warehouses enables efficient placement of products and improvement of working …
warehouses enables efficient placement of products and improvement of working …
Improving multi-target multi-camera tracking by track refinement and completion
Multi-camera tracking of vehicles on a city-wide level is a core component of modern traffic
monitoring systems. For this task, single-camera tracking failures are the most common …
monitoring systems. For this task, single-camera tracking failures are the most common …
Detecting vehicles on the edge: Knowledge distillation to improve performance in heterogeneous road traffic
The drastic growth in the number of vehicles in the last few decades has necessitated
significantly better traffic management and planning. To manage the traffic efficiently, traffic …
significantly better traffic management and planning. To manage the traffic efficiently, traffic …
Tracked-vehicle retrieval by natural language descriptions with domain adaptive knowledge
This paper introduces our solution for Track 2 in AI City Challenge 2022. Track 2 task is
TrackedVehicle Retrieval by Natural Language Descriptions with a real-world dataset with …
TrackedVehicle Retrieval by Natural Language Descriptions with a real-world dataset with …
A vision-based real-time traffic flow monitoring system for road intersections
In this study, a vision based real-time traffic flow monitoring system has been developed to
extract statistics passes through the intersections. A novel object tracking and data …
extract statistics passes through the intersections. A novel object tracking and data …
Multi-camera multi-vehicle tracking with domain generalization and contextual constraints
In this paper, we develop and propose a system for Multi-Camera Multi-Target (MCMT)
Vehicle Tracking in Track 1 of AI City Challenge 2022. There are many technical difficulties …
Vehicle Tracking in Track 1 of AI City Challenge 2022. There are many technical difficulties …
Performance evaluation of deep learning models on embedded platform for edge ai-based real time traffic tracking and detecting applications
HT Minh, L Mai, TV Minh - 2021 15th International Conference …, 2021 - ieeexplore.ieee.org
Edge Artificial Intelligence based traffic tracking and detecting sensors are very essential for
smart cities, especially for smart transportation applications. These sensors are not only …
smart cities, especially for smart transportation applications. These sensors are not only …