TMBuD: A dataset for urban scene building detection

TL;DR

This paper introduces TMBuD, a new dataset of 160 urban street view images from Timisoara, designed to improve building detection, edge evaluation, and semantic segmentation in urban scene image processing.

Contribution

The paper presents a novel dataset tailored for urban building detection and segmentation, facilitating better evaluation of algorithms in street view urban scenarios.

Findings

Dataset contains 160 high-resolution images from Timisoara.

Enables evaluation of edge detection and semantic segmentation algorithms.

Supports urban scene understanding in computer vision applications.

Abstract

Building recognition and 3D reconstruction of human made structures in urban scenarios has become an interesting and actual topic in the image processing domain. For this research topic the Computer Vision and Augmented Reality areas intersect for creating a better understanding of the urban scenario for various topics. In this paper we aim to introduce a dataset solution, the TMBuD, that is better fitted for image processing on human made structures for urban scene scenarios. The proposed dataset will allow proper evaluation of salient edges and semantic segmentation of images focusing on the street view perspective of buildings. The images that form our dataset offer various street view perspectives of buildings from urban scenarios, which allows for evaluating complex algorithms. The dataset features 160 images of buildings from Timisoara, Romania, with a resolution of 768 x 1024 pixels each.