Shehzad Afzal, Sohaib Ghani, Mohamad Mazen Hittawe, Sheikh Faisal Rashid, Omar M. Knio, Markus Hadwiger, Ibrahim Hoteit
{"title":"Visualization and Visual Analytics Approaches for Image and Video Datasets: A Survey","authors":"Shehzad Afzal, Sohaib Ghani, Mohamad Mazen Hittawe, Sheikh Faisal Rashid, Omar M. Knio, Markus Hadwiger, Ibrahim Hoteit","doi":"https://dl.acm.org/doi/10.1145/3576935","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":48574,"journal":{"name":"ACM Transactions on Interactive Intelligent Systems","volume":"59 2","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2023-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Interactive Intelligent Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/https://dl.acm.org/doi/10.1145/3576935","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
The ACM Transactions on Interactive Intelligent Systems (TiiS) publishes papers on research concerning the design, realization, or evaluation of interactive systems that incorporate some form of machine intelligence. TIIS articles come from a wide range of research areas and communities. An article can take any of several complementary views of interactive intelligent systems, focusing on:
the intelligent technology,
the interaction of users with the system, or
both aspects at once.