In topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse–Smale complexes play an essential role in capturing the shape of scalar field data. We present a state-of-the-art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time-varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational pro...
This doctoral dissertation explores and advances topology-based data analysis and visualization, a f...
Topological Data Analysis provides us with low-dimensional, topological descriptions of various type...
When visualizing data, we would like to convey both the data and the uncertainty associated with it....
In topological data analysis and visualization, topological descriptors such as persistence diagrams...
Scalar fields occur quite commonly in several application areas in both static and time-dependent fo...
Scientific visualization aims at helping users (i) abstract, (ii) interact with and (iii) analyze si...
Scientific phenomena are often studied through collections of related scalar fields such as data gen...
Scalar fields are used to represent physical quantities measured over a domain of interest. Study of...
This thesis discusses several applications of computational topology to the visualization of scalar...
This survey paper provides an overview of topological visualisation techniques for scalar data sets....
The complexity in visualizing volumetric data often limits the scope of direct exploration of scalar...
Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis b...
Identifying symmetry in scalar fields is a recent area of research in scientific visualization and c...
This survey paper provides an overview of topological visualisation techniques for scalar data sets....
Topological methods have been successfully used to identify features in scalar fields and to measure...
This doctoral dissertation explores and advances topology-based data analysis and visualization, a f...
Topological Data Analysis provides us with low-dimensional, topological descriptions of various type...
When visualizing data, we would like to convey both the data and the uncertainty associated with it....
In topological data analysis and visualization, topological descriptors such as persistence diagrams...
Scalar fields occur quite commonly in several application areas in both static and time-dependent fo...
Scientific visualization aims at helping users (i) abstract, (ii) interact with and (iii) analyze si...
Scientific phenomena are often studied through collections of related scalar fields such as data gen...
Scalar fields are used to represent physical quantities measured over a domain of interest. Study of...
This thesis discusses several applications of computational topology to the visualization of scalar...
This survey paper provides an overview of topological visualisation techniques for scalar data sets....
The complexity in visualizing volumetric data often limits the scope of direct exploration of scalar...
Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis b...
Identifying symmetry in scalar fields is a recent area of research in scientific visualization and c...
This survey paper provides an overview of topological visualisation techniques for scalar data sets....
Topological methods have been successfully used to identify features in scalar fields and to measure...
This doctoral dissertation explores and advances topology-based data analysis and visualization, a f...
Topological Data Analysis provides us with low-dimensional, topological descriptions of various type...
When visualizing data, we would like to convey both the data and the uncertainty associated with it....