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 …
Anomaly detection in traffic surveillance videos with gan-based future frame prediction
It is essential to develop efficient methods to detect abnormal events, such as car-crashes or
stalled vehicles, from surveillance cameras to provide in-time help. This motivates us to …
stalled vehicles, from surveillance cameras to provide in-time help. This motivates us to …
Estimating vehicle and pedestrian activity from town and city traffic cameras
L Chen, I Grimstead, D Bell, J Karanka, L Dimond… - Sensors, 2021 - mdpi.com
Traffic cameras are a widely available source of open data that offer tremendous value to
public authorities by providing real-time statistics to understand and monitor the activity …
public authorities by providing real-time statistics to understand and monitor the activity …
[PDF][PDF] Vehicle re-identification with learned representation and spatial verification and abnormality detection with multi-adaptive vehicle detectors for traffic video …
Traffic flow analysis is essential for intelligent transportation systems. In this paper, we
propose methods for two challenging problems in traffic flow analysis: vehicle re …
propose methods for two challenging problems in traffic flow analysis: vehicle re …
End-to-end learning for inter-vehicle distance and relative velocity estimation in ADAS with a monocular camera
Inter-vehicle distance and relative velocity estimations are two basic functions for any ADAS
(Advanced driver-assistance systems). In this paper, we propose a monocular camera …
(Advanced driver-assistance systems). In this paper, we propose a monocular camera …
A framework for real-time vehicle counting and velocity estimation using deep learning
To better control traffic and promote environmental sustainability, this study proposed a
framework to monitor vehicle number and velocity at real time. First, You Only Look Once-v4 …
framework to monitor vehicle number and velocity at real time. First, You Only Look Once-v4 …
Learning nanoscale motion patterns of vesicles in living cells
Detecting and analyzing nanoscale motion patterns of vesicles, smaller than the microscope
resolution (250 nm), inside living biological cells is a challenging problem. State-of-the-art …
resolution (250 nm), inside living biological cells is a challenging problem. State-of-the-art …
Traffic video event retrieval via text query using vehicle appearance and motion attributes
Traffic event retrieval is one of the important tasks for intelligent traffic system management.
To find accurate candidate events in traffic videos corresponding to a specific text query, it is …
To find accurate candidate events in traffic videos corresponding to a specific text query, it is …
Contextual detection of pedestrians and vehicles in orthophotography by fusion of deep learning algorithms
In the context of smart cities, monitoring pedestrian and vehicle movements is essential to
recognize abnormal events and prevent accidents. The proposed method in this work …
recognize abnormal events and prevent accidents. The proposed method in this work …
End-to-End Traffic Flow Rate Estimation From Compressed Video Streams
B Deguerre, C Chatelain… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Automatic traffic surveillance usually relies on the estimation of traffic flow parameters
through either dedicated sensors or the processing of road surveillance cameras. However …
through either dedicated sensors or the processing of road surveillance cameras. However …