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Bekleme Süresi Tahmini için Gerçek-zamanli Bir Kuyruk Takip Yöntemi

  • Eskisehir Technical University

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıHakem

1 Atıf (Scopus)

Özet

In daily life, people spend a significant part of their time waiting in queues at numerous places such as banks, airports, cafeterias and market cash registers. Various queue analysis and management tools have been developed to reduce this wasted time. One of these tools is the systems that analyze the queues and calculate the average waiting time. In this study, a computer vision method that calculates the average waiting time by detecting and tracking the people waiting in the queue is proposed. Thanks to this method, it is aimed that people can see how long they will wait before queuing. In the developed method, people waiting in a direction were analyzed by using object detection methods, and the times of joining and leaving the queue were tried to be determined. Due to the high processing load of the object detection algorithms, object tracking algorithms are used so that the method can work in real-time. The method developed according to the experimental studies can process the 640×480 resolution video on a mid-level GPU with %88.46 accuracy and speeds up to 95.51 fps.

Tercüme edilen katkı başlığıA Real-time Queue Tracking Method for Waiting Time Estimation
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı2022 30th Signal Processing and Communications Applications Conference, SIU 2022
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781665450928
DOI'lar
Yayın durumuYayınlandı - 2022
Harici olarak yayınlandıEvet
Etkinlik30th Signal Processing and Communications Applications Conference, SIU 2022 - Safranbolu, Türkiye
Süre: 15 May 202218 May 2022

Yayın serisi

Adı2022 30th Signal Processing and Communications Applications Conference, SIU 2022

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???event.eventtypes.event.conference???30th Signal Processing and Communications Applications Conference, SIU 2022
Ülke/BölgeTürkiye
ŞehirSafranbolu
Periyot15/05/2218/05/22

Bibliyografik not

Publisher Copyright:
© 2022 IEEE.

Keywords

  • MOSSE
  • Queue detection and analysis
  • YOLOv4
  • object tracking and detection

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