標題: Who Is the Designer? ARC-100 Database and Benchmark on Architecture Classification
作者: Huang, Yen-Chang
Wang, Shih-Yuan
Liong, Sze-Teng
Huang, Chieh-En
Hsieh, Yi-Chen
Wang, Hsiang-Yu
Lin, Wen-Hung
Gan, Y. S.
建築研究所
Institude of Architecture
關鍵字: Architecture;Building;Classification;Segmentation;CNN
公開日期: 1-Jan-2020
摘要: Architecture is about evolution, there exist many types of architectural styles that depend on the geography, traditions, and culture of the particular regions. An architectural designer may have a similar preference in creating the new architectural building, which can be easily recognized from the physical attributes and characteristics. This paper performs an architect classification based on the outward appearance of the building. An architecture database with 100 images (ARC-100) that have balanced class distribution is constructed. Among the architectural buildings, the best performance is 71% for 5-class classification. Convolutional neural networks (CNNs) have demonstrated breakthrough performance on various classification tasks in recent studies, and even outperform human experts in specific tasks. Thus, for the baseline evaluation, multiple pretrained CNN models are employed with slight modifications. Prior to the feature extraction and classification processes, the removal of background noise is performed using two approaches: manually and automatically. The former approach requires high human intervention, while the latter utilizes the cutting-edge object segmentation technology, namely mask regional convolutional neural network (R-CNN). The illustration of the experiment training progress and the confusion matrix are reported, to allow further interpretation and analysis for the model trained. Notably, this is the first work that performs automatic classification based on architectural styles. This framework can be used to improve the cultural understanding and practices in providing education for holistic development and enhance the learning experience and progressions from an aesthetic perspective. (C) 2020 The Authors. Published by Atlantis Press B.V.
URI: http://dx.doi.org/10.2991/ijcis.d.200824.001
http://hdl.handle.net/11536/155393
ISSN: 1875-6891
DOI: 10.2991/ijcis.d.200824.001
期刊: INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
Volume: 13
Issue: 1
起始頁: 1305
結束頁: 1314
Appears in Collections:Articles