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Cau Giay: A Dataset for Very Dense Building Extraction from Google Earth Imagery

Nguyen, Hoang Anh and Luu, Viet Hung and Phan, Anh and Bui, Quang Hung and Nguyen, Thi Nhat Thanh (2019) Cau Giay: A Dataset for Very Dense Building Extraction from Google Earth Imagery. In: 6th NAFOSTED Conference on Information and Computer Science, 12-13 December 2019, Hanoi, Vietnam.

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One of the major topics in photogrammetry is the automated extraction of building from data acquired by airborne sensors. What makes this task challenging is the very heterogeneous appearance and dense distribution of buildings in urban areas. While many dataset have been established, none of them pay attention to developing cities where buildings are not well planned. To complement the development of building extraction algorithms, a dataset of high resolution satellite image is constructed in this paper covering Cau Giay district, Hanoi, Vietnam. The dataset consists of 2100 images of size 1024 x 1024 pixels extracted from Google Earth. Shape, size, and construction material differ greatly from building to building, thus make it challenging for state-of-the-art algorithm to accurately extract building location. Some baselines are provided using Convolutional Neural Networks (CNNs). Experimental results show that U-Net model trained with Mean Square Error loss is able to achieve comparable results (OA=92.04).

Item Type: Conference or Workshop Item (Paper)
Subjects: Aerospace Engineering
Information Technology (IT)
Divisions: Center of Multidisciplinary Integrated Technologies for Field Monitoring (FIMO)
Faculty of Information Technology (FIT)
School of Aerospace Engineering (SAE)
Depositing User: Lưu Vi�t Hưng
Date Deposited: 09 Nov 2019 02:56
Last Modified: 09 Nov 2019 02:56

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