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

What is it about?

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.

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Why is it important?

Advances in AI have significantly improved the state of the art in computer vision, but have simultaneously posed new challenges for visualization and visual analytics researchers to develop new visualization techniques and frameworks to address these challenges. This mandates a systematic review of the current state of the art at the intersection of image and video analysis and visualization research to identify the gaps that exist between the requirements of the two domains, and explore opportunities for future research.