TY - JOUR
T1 - Visualization and Visual Analytics Approaches for Image and Video Datasets: A Survey
AU - Afzal, Shehzad
AU - Ghani, Sohaib
AU - Hittawe, Mohamad
AU - Rashid, Sheikh Faisal
AU - Knio, Omar
AU - Hadwiger, Markus
AU - Hoteit, Ibrahim
N1 - KAUST Repository Item: Exported on 2023-04-10
Acknowledged KAUST grant number(s): REP/1/3268-01-01
Acknowledgements: This study was supported by the Office of Sponsored Research (OSR) at King Abdullah University of Science and Technology (KAUST) under the “Virtual Red Sea Initiative” (award #REP/1/3268-01-01). We also thank the KAUST Visualization Core Lab for their help and support.
PY - 2023/3/9
Y1 - 2023/3/9
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/690912
UR - https://dl.acm.org/doi/10.1145/3576935
U2 - 10.1145/3576935
DO - 10.1145/3576935
M3 - Article
SN - 2160-6463
VL - 13
SP - 1
EP - 41
JO - ACM Transactions on Interactive Intelligent Systems
JF - ACM Transactions on Interactive Intelligent Systems
IS - 1
ER -