Multi-view multi-object tracking in an intelligent transportation system: A literature review

Rosario, Jay Robert B. del; Dadios, Elmer P.

doi:10.1109/hnicem.2017.8269524

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…In the review done by Wang [31], he focused on intelligent multi‐camera video surveillance. The survey presented in [32] focused on multi‐view vision systems in various platforms. Walia and Kapoor [4] aimed at categorising multi‐cue tracking methods into single‐modal (by one type of source) and multi‐modal (combining different types of sources).…”

Section: Related Workmentioning

confidence: 99%

Multi‐camera multiple vehicle tracking in urban intersections based on multilayer graphs

Delavarian

Marouzi

Hassanpour

et al. 2020

IET intell. transp. syst

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Section: Related Workmentioning

confidence: 99%

Multi‐camera multiple vehicle tracking in urban intersections based on multilayer graphs

Delavarian

Marouzi

Hassanpour

et al. 2020

IET intell. transp. syst

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“…As per [17], they used a different method for collision avoidance. Spline parameterization was applied to compute for the non-collision trajectories of the environment and can be used in linear and non-linear models.…”

Section: Review Of the Related Literaturementioning

confidence: 99%

A Modeling system on the Implementation of Automated Vehicles

Africa¹,

Pasia²,

Sy³

2020

IJETER

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As time pass-by, technology improves and innovates with it. The newly introduced autonomous vehicles have their capability to do different actions where no human intervention is needed, such as automatic parking and crash collision avoidance. This study is all about autonomous vehicles (AV) that are capable of traveling and operating in the Philippines. The researchers aimed to determine whether an AV is apt to work in the country, given the hindrances such as traffic and various driving and road conditions. To do that, they considered past studies that relate and may help in their research, such as the use of heading reference assisted pose and controllers. In analyzing the data, they made block models of their study that considers the given circumstances such as traffic and road -for instance, a block diagram if the AV is in an undeveloped area and if the AV is at an intersection. Following the data gathered and considering the block diagrams, the students conclude that the Philippines is not yet ready for autonomous vehicles. Lastly, the researchers give suggestions that may be keys for AV to work in the Philippines.

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“…15 In their proposed method, virtual entry or exit is used to improve the prediction of vehicle direction, when applied to the actual tracking, there are still problems of missing tracking and false tracking, and the real-time performance of target tracking can’t be guaranteed, and the tracking rate is relatively low. Del Rosario et al 16 and others focused on intelligent camera video monitoring, and proposed that data can be associated with multi-view vision systems on various platforms, it can improve the accuracy of vehicle detection in the presence of obstacles, but for the case of vehicle trajectory crossing, there will still be target tracking error.…”

Section: Introductionmentioning

confidence: 99%

Road intersections vehicle tracking based on multi-layer graphs and multi-angle

Liu

Yan

Yang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Aiming at the problem of tracking uncertain vehicle motion flow at intersections, a method based on multi-level graphs and multi-angle is proposed. Firstly, each motion flow is assigned to different layers with diverse neighborhoods by using the constructed multi-layer graphs. Secondly, all multi-layer graphics under multi-angle views are mapped to the selected main view. Finally, the vehicle tracking is realized by solving the shortest path of the mapping main view motion flow. Through the experiment and analysis of vehicle tracking at intersections, the results show that this method can effectively predict vehicle trajectory for uncertain vehicle flow at intersections, and the misjudgment rate between tracking effect and the real situation on the ground is less than 6%, which can provide a new method for vehicle tracking in intelligent transportation.

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Multi-view multi-object tracking in an intelligent transportation system: A literature review

Cited by 8 publications

References 11 publications

Multi‐camera multiple vehicle tracking in urban intersections based on multilayer graphs

Multi‐camera multiple vehicle tracking in urban intersections based on multilayer graphs

A Modeling system on the Implementation of Automated Vehicles

Road intersections vehicle tracking based on multi-layer graphs and multi-angle

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