TMBuD: A dataset for urban scene building detection
This provides a new dataset for researchers in computer vision and augmented reality working on urban scene analysis, but it is incremental as it adds to existing datasets.
The authors introduced TMBuD, a dataset of 160 images (768 x 1024 pixels) from Timisoara, Romania, designed for building detection in urban scenes, enabling evaluation of salient edges and semantic segmentation algorithms.
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.