Building3D: An Urban-Scale Dataset and Benchmarks for Learning Roof Structures from Point Clouds

Urban modeling from LiDAR point clouds is an important topic in computer vision, computer graphics, photogrammetry and remote sensing. 3D city models have found a wide range of applications in smart cities, autonomous navigation, urban planning and mapping etc. However, existing datasets for 3D modeling mainly focus on common objects such as furniture or cars. Lack of building datasets has become a major obstacle for applying deep learning technology to specific domains such as urban modeling. In this paper, we present a urban-scale dataset consisting of more than 160 thousands buildings along with corresponding point clouds, mesh and wire-frame models, covering 16 cities in Estonia about 998 Km2. We extensively evaluate performance of state-of-the-art algorithms including handcrafted and deep feature based methods. Experimental results indicate that Building3D has challenges of high intra-class variance, data imbalance and large-scale noises. The Building3D is the first and largest urban-scale building modeling benchmark, allowing a comparison of supervised and self-supervised learning methods. We believe that our Building3D will facilitate future research on urban modeling, aerial path planning, mesh simplification, and semantic/part segmentation etc

Inclusive interaction design: bridging the gap between information visualization perception and color vision deficiency users

It’s becoming increasingly important to design for Inclusivity, meaning building products that are accessible to all type of users, namely color vision deficiency (CVD) deuteranope users. Along with that, we can say that Information Visualization plays a big role in the understanding of how ou world functions, since the amount of produced data (2.5 exabytes) is increasing every day. In this way, this project aims to bridge the gap between Information Visualization perception and color vision deficiency users, by exploring the effects that saturation as a variable, applied through an interaction design methodology approach, has on human visual perception. An interactive system was designe in order to explore the effects saturation had in both user’s perception. To perform the experiment, 12 trichromatic male participants were recruited and the selected graph’s colours were simulated into colours a CVD user would normally perceive. This experiment enabled to reach a range in which both trichromatic and CVD users perceive the information of a specific graph in an optimal way. Serving as a first assessment in potentially reaching a range that ensures the optimal visual perception of all types of Information Visualizations for both CVD an trichromatic users, this project intends to be used as a reference in future investigations, in order to improve the quality of life of users affected by this visual constraint