Feature Tracking by Two-Step Optimization

Schnorr, Andrea; Helmrich, Dirk N.; Denker, Dominik; Kuhlen, Torsten; Hentschel, Bernd

doi:10.1109/tvcg.2018.2883630

Cited by 20 publications

(12 citation statements)

References 31 publications

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“…Another interesting idea would be to employ user guided classification of critical points into relevant and non-relevant features in a few selected time steps, and using learning algorithms to automatically extract relevant features in the complete time series. To improve the feature configuration and feature tracks, there are a lot of ideas in the literature, for example, to consider global optimization criteria for the tracks similar as proposed by Saikia et al [17] or Schnorr et al [19]. For this, a better interface for designing rules to be used as feature descriptors is required.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…While these methods are valuable, they often cannot directly be applied to solve an application-specific tracking problem. On the other hand, there are methods inspired by applications proposing very specific algorithms for a fixed feature definition, for example for dissipation elements [18] or tracking of cyclones [22]. Even though these approaches work well in one setting, they often miss the necessary flexibility to be useful in a larger context.…”

Section: Introductionmentioning

confidence: 99%

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Topology-Based Feature Design and Tracking for Multi-Center Cyclones

Engelke¹,

Masood²,

Beran³

et al. 2020

Preprint

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In this paper, we propose a concept to design, track, and compare application-specific feature definitions expressed as sets of critical points. Our work has been inspired by the observation that in many applications a large variety of different feature definitions for the same concept are used. Often, these definitions compete with each other and it is unclear which definition should be used in which context. A prominent example is the definition of cyclones in climate research. Despite the differences, frequently these feature definitions can be related to topological concepts.In our approach, we provide a cyclone tracking framework that supports interactive feature definition and comparison based on a precomputed tracking graph that stores all extremal points as well as their temporal correspondents. The framework combines a set of independent building blocks: critical point extraction, critical point tracking, feature definition, and track exploration. One of the major advantages of such an approach is the flexibility it provides, that is, each block is exchangeable. Moreover, it also enables us to perform the most expensive analysis, the construction of a full tracking graph, as a prepossessing step, while keeping the feature definition interactive. Different feature definitions can be explored and compared interactively based on this tracking graph. Features are specified by rules for grouping critical points, while feature tracking corresponds to filtering and querying the full tracking graph by specific requests. We demonstrate this method for cyclone identification and tracking in the context of climate research.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Topology-Based Feature Design and Tracking for Multi-Center Cyclones

Engelke¹,

Masood²,

Beran³

et al. 2020

Preprint

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“…Schnorr et al . [SHD∗20] presented a two‐step tracking approach for space‐filling features (objects whose union covers the domain). The work was motivated by the analysis of dissipation elements, which are defined as Morse‐Smale cells (Sect.…”

Section: Visualization Tasks For Time‐varying Fieldsmentioning

confidence: 99%

Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization

Yan

Masood

Sridharamurthy

et al. 2021

Computer Graphics Forum

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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 properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures.

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“…A DE is defined as the spatial region from which the same pair of maximum and minimum points is reached by scalar gradient trajectories. Within this region, the scalar field is monotonic making DEs equivalent to Morse-Smale complexes in topology (Schnorr et al 2020). This method of identification of DEs is shown in a schematic fashion in figure 1.…”

Section: Maximum Minimummentioning

confidence: 99%

“…Within this region, the scalar field is monotonic making DEs equivalent to Morse–Smale complexes in topology (Schnorr et al. 2020). This method of identification of DEs is shown in a schematic fashion in figure 1.…”

Section: Introductionmentioning

confidence: 99%