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

Translated title of the contribution: Human Detection with Fisheye Camera

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

Department of Electronics and Communication Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Translated title of the contribution	Human Detection with Fisheye Camera
Original language	Turkish
Title of host publication	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350343557
DOIs	https://doi.org/10.1109/SIU59756.2023.10223840
Publication status	Published - 2023
Event	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 - Istanbul, Turkey Duration: 5 Jul 2023 → 8 Jul 2023

Publication series

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

Conference

Conference	31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023
Country/Territory	Turkey
City	Istanbul
Period	5/07/23 → 8/07/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Access to Document

10.1109/SIU59756.2023.10223840

Cite this

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

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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.",

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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",

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

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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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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

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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

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