QuteVis: Visually Studying Transportation Patterns Using Multisketch Query of Joint Traffic Situations. Academic Article

abstract

• QuteVis uses multisketch query and visualization to discover specific times and days in history with specified joint traffic patterns at different city locations. Users can use touch input devices to define, edit, and modify multiple sketches on a city map. A set of visualizations and interactions is provided to help users browse and compare retrieved traffic situations and discover potential influential factors. QuteVis is built upon a transport database that integrates heterogeneous data sources with an optimized spatial indexing and weighted similarity computation. An evaluation with real-world data and domain experts demonstrates that QuteVis is useful in urban transportation applications in modern cities.

authors

• Ye, Xinyue

published proceedings

• IEEE Comput Graph Appl

author list (cited authors)

• Al-Dohuki, S., Zhao, Y. e., Kamw, F., Yang, J., Ye, X., & Chen, W.

citation count

• 5

complete list of authors

• Al-Dohuki, Shamal||Zhao, Ye||Kamw, Farah||Yang, Jing||Ye, Xinyue||Chen, Wei

publication date

• March 2021

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Computer Graphics and Applications  Journal

keywords

• 11 Sustainable Cities And Communities
• 46 Information And Computing Sciences
• 4603 Computer Vision And Multimedia Computation
• 4607 Graphics, Augmented Reality And Games
• 4608 Human-centred Computing

PubMed Central ID

• 30990422

Digital Object Identifier (DOI)

• 10.1109/MCG.2019.2911230

start page

• 35

end page

• 48

volume

• 41

issue

• 2

URL

• http://dx.doi.org/10.1109/mcg.2019.2911230

user-defined tag

• 11 Sustainable Cities and Communities