Visualization and Visual Analytics Approaches for Image and Video Datasets: A Survey

Author:

Afzal Shehzad1ORCID,Ghani Sohaib1ORCID,Hittawe Mohamad Mazen1ORCID,Rashid Sheikh Faisal2ORCID,Knio Omar M.1ORCID,Hadwiger Markus1ORCID,Hoteit Ibrahim1ORCID

Affiliation:

1. King Abdullah University of Science and Technology, Makkah, Saudi Arabia

2. German Research Center for Artificial Intelligence (DFKI), Berlin, Germany

Abstract

Image and video data analysis has become an increasingly important research area with applications in different domains such as security surveillance, healthcare, augmented and virtual reality, video and image editing, activity analysis and recognition, synthetic content generation, distance education, telepresence, remote sensing, sports analytics, art, non-photorealistic rendering, search engines, and social media. Recent advances in Artificial Intelligence (AI) and particularly deep learning have sparked new research challenges and led to significant advancements, especially in image and video analysis. These advancements have also resulted in significant research and development in other areas such as visualization and visual analytics, and have created new opportunities for future lines of research. In this survey article, we present the current state of the art at the intersection of visualization and visual analytics, and image and video data analysis. We categorize the visualization articles included in our survey based on different taxonomies used in visualization and visual analytics research. We review these articles in terms of task requirements, tools, datasets, and application areas. We also discuss insights based on our survey results, trends and patterns, the current focus of visualization research, and opportunities for future research.

Funder

Office of Sponsored Research

King Abdullah University of Science and Technology

Virtual Red Sea Initiative

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

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