Visualization and Visual Analysis of Multimedia Data in Manufacturing: A Survey

Yunchao Wang, Zihao Zhu, Lei Wang, Guodao Sun, Ronghua Liang

This github repo hosts a web-based interactive browser of our survey paper on "MMDM", which is accepted by ChinaVis 2022.

This survey is published at Visual Informaticvs, link.

Online interactive browser: https://zjutvis.github.io/MMDM/

Abstract

With the development of production technology and social needs, sectors of manufacturing are constantly improving. The use of sensors and computers has made it increasingly convenient to collect multimedia data in manufacturing. Targeted, rapid, and detailed analysis based on the type of multimedia data can make timely decisions at different stages of the entire manufacturing process. Visualization and visual analytics are frequently adopted in multimedia data analysis of manufacturing because of their powerful ability to understand, present, and analyze data intuitively and interactively. In this paper, we present a literature review of visualization and visual analytics specifically for manufacturing multimedia data. We classify existing research according to visualization techniques, interaction analysis methods, and application areas. We discuss the differences when visualization and visual analytics are applied to different types of multimedia data in the context of particular examples of manufacturing research projects. Finally, we summarize the existing challenges and prospective research directions.

Citation

@article{WANG202212,
  title = {Visualization and visual analysis of multimedia data in manufacturing: A survey},
  journal = {Visual Informatics},
  volume = {6},
  number = {4},
  pages = {12-21},
  year = {2022},
  author = {Yunchao Wang and Zihao Zhu and Lei Wang and Guodao Sun and Ronghua Liang}
}