The State of the Art in Visual Analytics for 3D Urban Data
- URL: http://arxiv.org/abs/2404.15976v1
- Date: Wed, 24 Apr 2024 16:50:42 GMT
- Title: The State of the Art in Visual Analytics for 3D Urban Data
- Authors: Fabio Miranda, Thomas Ortner, Gustavo Moreira, Maryam Hosseini, Milena Vuckovic, Filip Biljecki, Claudio Silva, Marcos Lage, Nivan Ferreira,
- Abstract summary: Urbanization has amplified the importance of three-dimensional structures in urban environments.
With the growing availability of 3D urban data, numerous studies have focused on developing visual analysis techniques tailored to the unique characteristics of urban environments.
incorporating the third dimension into visual analytics introduces additional challenges in designing effective visual tools to tackle urban data's diverse complexities.
- Score: 5.056350278679641
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Urbanization has amplified the importance of three-dimensional structures in urban environments for a wide range of phenomena that are of significant interest to diverse stakeholders. With the growing availability of 3D urban data, numerous studies have focused on developing visual analysis techniques tailored to the unique characteristics of urban environments. However, incorporating the third dimension into visual analytics introduces additional challenges in designing effective visual tools to tackle urban data's diverse complexities. In this paper, we present a survey on visual analytics of 3D urban data. Our work characterizes published works along three main dimensions (why, what, and how), considering use cases, analysis tasks, data, visualizations, and interactions. We provide a fine-grained categorization of published works from visualization journals and conferences, as well as from a myriad of urban domains, including urban planning, architecture, and engineering. By incorporating perspectives from both urban and visualization experts, we identify literature gaps, motivate visualization researchers to understand challenges and opportunities, and indicate future research directions.
Related papers
- 3D Gaussian Splatting: Survey, Technologies, Challenges, and Opportunities [57.444435654131006]
3D Gaussian Splatting (3DGS) has emerged as a prominent technique with the potential to become a mainstream method for 3D representations.
This survey aims to analyze existing 3DGS-related works from multiple intersecting perspectives.
arXiv Detail & Related papers (2024-07-24T16:53:17Z) - Data Augmentation in Human-Centric Vision [54.97327269866757]
This survey presents a comprehensive analysis of data augmentation techniques in human-centric vision tasks.
It delves into a wide range of research areas including person ReID, human parsing, human pose estimation, and pedestrian detection.
Our work categorizes data augmentation methods into two main types: data generation and data perturbation.
arXiv Detail & Related papers (2024-03-13T16:05:18Z) - A Comprehensive Survey of 3D Dense Captioning: Localizing and Describing
Objects in 3D Scenes [80.20670062509723]
3D dense captioning is an emerging vision-language bridging task that aims to generate detailed descriptions for 3D scenes.
It presents significant potential and challenges due to its closer representation of the real world compared to 2D visual captioning.
Despite the popularity and success of existing methods, there is a lack of comprehensive surveys summarizing the advancements in this field.
arXiv Detail & Related papers (2024-03-12T10:04:08Z) - Unified Data Management and Comprehensive Performance Evaluation for
Urban Spatial-Temporal Prediction [Experiment, Analysis & Benchmark] [78.05103666987655]
This work addresses challenges in accessing and utilizing diverse urban spatial-temporal datasets.
We introduceatomic files, a unified storage format designed for urban spatial-temporal big data, and validate its effectiveness on 40 diverse datasets.
We conduct extensive experiments using diverse models and datasets, establishing a performance leaderboard and identifying promising research directions.
arXiv Detail & Related papers (2023-08-24T16:20:00Z) - The Urban Toolkit: A Grammar-based Framework for Urban Visual Analytics [5.674216760436341]
The complex nature of urban issues and the overwhelming amount of available data have posed significant challenges in translating these efforts into actionable insights.
When analyzing a feature of interest, an urban expert must transform, integrate, and visualize different thematic (e.g., sunlight access, demographic) and physical (e.g., buildings, street networks) data layers.
This makes the entire visual data exploration and system implementation difficult for programmers and also sets a high entry barrier for urban experts outside of computer science.
arXiv Detail & Related papers (2023-08-15T13:43:04Z) - Urban Visual Intelligence: Studying Cities with AI and Street-level
Imagery [12.351356101876616]
This paper reviews the literature on the appearance and function of cities to illustrate how visual information has been used to understand them.
A conceptual framework, Urban Visual Intelligence, is introduced to elaborate on how new image data sources and AI techniques are reshaping the way researchers perceive and measure cities.
arXiv Detail & Related papers (2023-01-02T10:00:26Z) - A Comparison of Spatiotemporal Visualizations for 3D Urban Analytics [7.157706457130007]
This paper investigates how effective 3D urban visual analytics are at supportingtemporal analysis on building surfaces.
We compare four representative visual designs used to visualize 3Dtemporal urban data: spatial juxtaposition, temporal juxtaposition, linked view, and embedded view.
Our results demonstrate that participants were more accurate using plot-based visualizations but faster using colorcoded visualizations.
arXiv Detail & Related papers (2022-08-10T14:38:13Z) - GANs for Urban Design [0.0]
The topic investigated in this paper is the application of Generative Adversarial Networks to the design of an urban block.
The research presents a flexible model able to adapt to the morphological characteristics of a city.
arXiv Detail & Related papers (2021-05-04T19:50:24Z) - Methodological Foundation of a Numerical Taxonomy of Urban Form [62.997667081978825]
We present a method for numerical taxonomy of urban form derived from biological systematics.
We derive homogeneous urban tissue types and, by determining overall morphological similarity between them, generate a hierarchical classification of urban form.
After framing and presenting the method, we test it on two cities - Prague and Amsterdam.
arXiv Detail & Related papers (2021-04-30T12:47:52Z) - Urban land-use analysis using proximate sensing imagery: a survey [3.79474411753363]
Studies leveraging proximate sensing imagery have demonstrated great potential to address the need for local data in urban land-use analysis.
This paper reviews and summarizes the state-of-the-art methods and publicly available datasets from proximate sensing to support land-use analysis.
arXiv Detail & Related papers (2021-01-13T01:30:21Z) - Survey on Visual Sentiment Analysis [87.20223213370004]
This paper reviews pertinent publications and tries to present an exhaustive overview of the field of Visual Sentiment Analysis.
The paper also describes principles of design of general Visual Sentiment Analysis systems from three main points of view.
A formalization of the problem is discussed, considering different levels of granularity, as well as the components that can affect the sentiment toward an image in different ways.
arXiv Detail & Related papers (2020-04-24T10:15:22Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.