Predicting Various Architectural Styles Using Computer Vision Methods

Meryem Öztürkoğlu

doi:10.30785/mbud.1334044

TR EN

Computer Vision Metodlarıyla Çeşitli Mimari Üslupların Tahmin Edilmesi

Abstract

Yapay zeka (AI) alanının alt dalı olan Computer Vision (bilgisayar görüşü, CV), bilgisayarların görsel verileri işleyerek nesneleri tanıyabilmesine olanak sağlar. CV, otomotiv, gıda endüstrisi, hastalıkların teşhisi gibi alanlarda yaygın kullanılmaktadır. AI bunu yaparken, algoritmaları kullanmaktadır. Nesne algılamaya dayalı algoritmaların en önemlilerinden biri yüksek veri işleme hızıyla daha net sonuçlar veren YOLO (You Only Look Once) dur. Bu çalışmanın amacı, temel alınan videodaki öne çıkan yapıların gotik, barok, palladyen, art nouveau mimari üsluplarından hangisine ait olduğunu belirlemeye yönelik nesne algılama tabanlı CV projesi gerçekleştirmektir. Çalışma veri seti oluşturma, veri etiketleme, model oluşturma ve modelin eğitimi aşamalarından oluşmaktadır. Veri etiketleme platformu olarak Roboflow, model oluşturma ve eğitim aşamaları için YOLOv8 kullanılmıştır. Süreç sonunda modelin mimari üslupları yüksek doğruluk payı ile kısa zamanda tahmin etmesi modelin başarılı gerçek zamanlı bir nesne algılama algoritması olduğunu ortaya koymuş, CV’ın mimarlık alanında da kullanılabileceği ve mimarlık ile ilgili diğer alanlara da katkı sunabileceği vurgulanmıştır.

Keywords

Computer vision, nesne algılama, YOLO, mimari üslup

Supporting Institution

yok

Project Number

yok

Thanks

Fatih Hattatoğlu, PhD., Müslüm Yıldız, MSc., Mustafa Erdoğan, MSc.

Predicting Various Architectural Styles Using Computer Vision Methods

Abstract

Computer Vision (CV), subfield of artificial intelligence (AI), enables computers to process visual data and recognize objects. CV is widely used in, automotive, food industry and diseases diagnosis. AI achieves this by algorithms. One of the important algorithms based on object detection is YOLO (You Only Look Once), provides more accurate results with high processing speed. The aim of this study is to perform an object detection-based CV project, to determine the structures in given video belong to one of the architectural styles: Gothic, Baroque, Palladian, or Art Nouveau. The study consists of data set creation, data labeling, model creation and model training. Roboflow was used as the data labeling platform and YOLOv8 was used for model building and training phases. At the end of the process, the fact that the model predicts architectural styles with high accuracy in a short time revealed that the model is a successful real-time object detection algorithm, and it was emphasized that CV can be used in the field of architecture and can contribute to other fields related to architecture.

Keywords

Computer vision, object detection, YOLO, architectural style

Project Number

yok

Thanks

The author wishes to thank Fatih Hattatoğlu, PhD., Müslüm Yıldız, MSc., Mustafa Erdoğan, MSc. for the suggestions that helped shape the work and thank the anonymous reviewers for their helpful comments. The paper complies with national and international research and publication ethics. Ethics committee approval was not required for this manuscript.

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Details

Primary Language

English

Subjects

Architectural Science and Technology, Architectural History, Theory and Criticism, Architectural Design, Materials and Technology in Architecture, Architecture (Other)

Journal Section

Research Article

Authors

Meryem Öztürkoğlu ^*
0009-0004-8420-6096
Türkiye

Publication Date

December 16, 2023

Submission Date

July 28, 2023

Acceptance Date

November 25, 2023

Published in Issue

Year 2023 Volume: 8 Number: 2

DOI

https://doi.org/10.30785/mbud.1334044

IZ

https://izlik.org/JA85ER58RC

APA

Öztürkoğlu, M. (2023). Predicting Various Architectural Styles Using Computer Vision Methods. Journal of Architectural Sciences and Applications, 8(2), 811-828. https://doi.org/10.30785/mbud.1334044

AMA

1.Öztürkoğlu M. Predicting Various Architectural Styles Using Computer Vision Methods. JASA. 2023;8(2):811-828. doi:10.30785/mbud.1334044

Chicago

Öztürkoğlu, Meryem. 2023. “Predicting Various Architectural Styles Using Computer Vision Methods”. Journal of Architectural Sciences and Applications 8 (2): 811-28. https://doi.org/10.30785/mbud.1334044.

EndNote

Öztürkoğlu M (December 1, 2023) Predicting Various Architectural Styles Using Computer Vision Methods. Journal of Architectural Sciences and Applications 8 2 811–828.

IEEE

[1]M. Öztürkoğlu, “Predicting Various Architectural Styles Using Computer Vision Methods”, JASA, vol. 8, no. 2, pp. 811–828, Dec. 2023, doi: 10.30785/mbud.1334044.

ISNAD

Öztürkoğlu, Meryem. “Predicting Various Architectural Styles Using Computer Vision Methods”. Journal of Architectural Sciences and Applications 8/2 (December 1, 2023): 811-828. https://doi.org/10.30785/mbud.1334044.

JAMA

1.Öztürkoğlu M. Predicting Various Architectural Styles Using Computer Vision Methods. JASA. 2023;8:811–828.

MLA

Öztürkoğlu, Meryem. “Predicting Various Architectural Styles Using Computer Vision Methods”. Journal of Architectural Sciences and Applications, vol. 8, no. 2, Dec. 2023, pp. 811-28, doi:10.30785/mbud.1334044.

Vancouver

1.Meryem Öztürkoğlu. Predicting Various Architectural Styles Using Computer Vision Methods. JASA. 2023 Dec. 1;8(2):811-28. doi:10.30785/mbud.1334044

Predicting Various Architectural Styles Using Computer Vision Methods

Computer Vision Metodlarıyla Çeşitli Mimari Üslupların Tahmin Edilmesi

Abstract

Keywords

Supporting Institution

Project Number

Thanks

Predicting Various Architectural Styles Using Computer Vision Methods

Abstract

Keywords

Project Number

Thanks

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite

Cited By

Predicting Various Architectural Styles Using Computer Vision Methods

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