Customized Atrous Spatial Pyramid Pooling with Joint Convolutions for Urban Tree Segmentation

Danilo Samuel Jodas, Danilo Samuel Jodas, Giuliana Velasco, Sergio Brazolin, Reinaldo Araujo de Lima, Leandro Passos, João Papa

2025

Abstract

Urban trees provide several benefits to the cities, including local climatic regulation and better life quality. Assessing the tree conditions is essential to gather important insights related to its biomechanics and the possible risk of falling. The common strategy is ruled by fieldwork campaigns to collect the tree’s physical measures like height, the trunk’s diameter, and canopy metrics for a first-glance assessment and further prediction of the possible risk to the city’s infrastructure. The canopy and trunk of the tree play an important role in the resistance analysis when exposed to severe windstorm events. However, fieldwork analysis is laborious and time-expensive because of the massive number of trees. Therefore, strategies based on computational analysis are highly demanded to promote a rapid assessment of tree conditions. This paper presents a deep learning-based approach for semantic segmentation of the trunk and canopy of trees in images acquired from the street-view perspective. The proposed strategy combines convolutional modules, spatial pyramid pooling, and attention mechanism into a U-Net-based architecture to improve the prediction capacity. Experiments performed over two image datasets showed the proposed model attained competitive results compared to previous works employing large-sized semantic segmentation models.

Paper Citation

in Harvard Style

Jodas D., Velasco G., Brazolin S., Araujo de Lima R., Passos L. and Papa J. (2025). Customized Atrous Spatial Pyramid Pooling with Joint Convolutions for Urban Tree Segmentation. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 267-274. DOI: 10.5220/0013090400003912

in Bibtex Style

@conference{visapp25,
author={Danilo Jodas and Giuliana Velasco and Sergio Brazolin and Reinaldo Araujo de Lima and Leandro Passos and João Papa},
title={Customized Atrous Spatial Pyramid Pooling with Joint Convolutions for Urban Tree Segmentation},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={267-274},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013090400003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Customized Atrous Spatial Pyramid Pooling with Joint Convolutions for Urban Tree Segmentation
SN - 978-989-758-728-3
AU - Jodas D.
AU - Velasco G.
AU - Brazolin S.
AU - Araujo de Lima R.
AU - Passos L.
AU - Papa J.
PY - 2025
SP - 267
EP - 274
DO - 10.5220/0013090400003912
PB - SciTePress