Balik Gözü Kamera ile Insan Tespiti

Abdullah Kaan Karsli; Ihsan Mert Muhaciroǧlu; Yasin Apalan; Tayfun Akgul

doi:10.1109/SIU59756.2023.10223840

Balik Gözü Kamera ile Insan Tespiti

Abdullah Kaan Karsli, Ihsan Mert Muhaciroǧlu, Yasin Apalan, Tayfun Akgul

Elektronik ve Hab.Müh.Bölümü

Istanbul Technical University

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

Özet

Most of the human detection and tracking studies in camera images are done by means of cameras with normal viewing angles. Detection and tracking in images of overhead cameras with fisheye angle of view involve various difficulties. Due to the wide field of view cameras with overhead view providing a 360° angle of view, the shapes of the objects on the edge of the image are distorted. Detection algorithms have difficulty detecting deformed objects. In this study, it is aimed to obtain a model suitable for fish-eye cameras by training human samples taken from fish-eye camera images with CNN algorithm and to measure the performance of the model with YOLO detection algorithm. A simple interface design has been made to facilitate the tracking of the image frames from the YOLO detection algorithm.

Tercüme edilen katkı başlığı	Human Detection with Fisheye Camera
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9798350343557
DOI'lar	https://doi.org/10.1109/SIU59756.2023.10223840
Yayın durumu	Yayınlandı - 2023
Etkinlik	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 - Istanbul, Turkey Süre: 5 Tem 2023 → 8 Tem 2023

Yayın serisi

Adı	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
Ülke/Bölge	Turkey
Şehir	Istanbul
Periyot	5/07/23 → 8/07/23

Bibliyografik not

Publisher Copyright:
© 2023 IEEE.

Keywords

detection algortihm
fisheye
fisheye camera
human detection
model

Belgeye Erişim

10.1109/SIU59756.2023.10223840

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Karsli, A. K., Muhaciroǧlu, I. M., Apalan, Y., & Akgul, T. (2023). Balik Gözü Kamera ile Insan Tespiti. In 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU59756.2023.10223840

@inproceedings{589bce9d6e934f0caa462e16f5f45b09,

title = "Balik G{\"o}z{\"u} Kamera ile Insan Tespiti",

abstract = "Most of the human detection and tracking studies in camera images are done by means of cameras with normal viewing angles. Detection and tracking in images of overhead cameras with fisheye angle of view involve various difficulties. Due to the wide field of view cameras with overhead view providing a 360° angle of view, the shapes of the objects on the edge of the image are distorted. Detection algorithms have difficulty detecting deformed objects. In this study, it is aimed to obtain a model suitable for fish-eye cameras by training human samples taken from fish-eye camera images with CNN algorithm and to measure the performance of the model with YOLO detection algorithm. A simple interface design has been made to facilitate the tracking of the image frames from the YOLO detection algorithm.",

keywords = "detection algortihm, fisheye, fisheye camera, human detection, model",

author = "Karsli, {Abdullah Kaan} and Muhaciroǧlu, {Ihsan Mert} and Yasin Apalan and Tayfun Akgul",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 ; Conference date: 05-07-2023 Through 08-07-2023",

year = "2023",

doi = "10.1109/SIU59756.2023.10223840",

language = "T{\"u}rk{\c c}e",

series = "31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023",

address = "United States",

}

Karsli, AK, Muhaciroǧlu, IM, Apalan, Y & Akgul, T 2023, Balik Gözü Kamera ile Insan Tespiti. in 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023, Institute of Electrical and Electronics Engineers Inc., 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023, Istanbul, Turkey, 5/07/23. https://doi.org/10.1109/SIU59756.2023.10223840

Balik Gözü Kamera ile Insan Tespiti. / Karsli, Abdullah Kaan; Muhaciroǧlu, Ihsan Mert; Apalan, Yasin et al.
31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023).

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

TY - GEN

T1 - Balik Gözü Kamera ile Insan Tespiti

AU - Karsli, Abdullah Kaan

AU - Muhaciroǧlu, Ihsan Mert

AU - Apalan, Yasin

AU - Akgul, Tayfun

PY - 2023

Y1 - 2023

N2 - Most of the human detection and tracking studies in camera images are done by means of cameras with normal viewing angles. Detection and tracking in images of overhead cameras with fisheye angle of view involve various difficulties. Due to the wide field of view cameras with overhead view providing a 360° angle of view, the shapes of the objects on the edge of the image are distorted. Detection algorithms have difficulty detecting deformed objects. In this study, it is aimed to obtain a model suitable for fish-eye cameras by training human samples taken from fish-eye camera images with CNN algorithm and to measure the performance of the model with YOLO detection algorithm. A simple interface design has been made to facilitate the tracking of the image frames from the YOLO detection algorithm.

AB - Most of the human detection and tracking studies in camera images are done by means of cameras with normal viewing angles. Detection and tracking in images of overhead cameras with fisheye angle of view involve various difficulties. Due to the wide field of view cameras with overhead view providing a 360° angle of view, the shapes of the objects on the edge of the image are distorted. Detection algorithms have difficulty detecting deformed objects. In this study, it is aimed to obtain a model suitable for fish-eye cameras by training human samples taken from fish-eye camera images with CNN algorithm and to measure the performance of the model with YOLO detection algorithm. A simple interface design has been made to facilitate the tracking of the image frames from the YOLO detection algorithm.

KW - detection algortihm

KW - fisheye

KW - fisheye camera

KW - human detection

KW - model

UR - http://www.scopus.com/inward/record.url?scp=85173530865&partnerID=8YFLogxK

U2 - 10.1109/SIU59756.2023.10223840

DO - 10.1109/SIU59756.2023.10223840

M3 - Konferans katkısı

AN - SCOPUS:85173530865

T3 - 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

BT - 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023

Y2 - 5 July 2023 through 8 July 2023

ER -

Balik Gözü Kamera ile Insan Tespiti

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap