Visual comparison for information visualization

Gleicher, Michael; Albers, Danielle; Walker, Rick; Jusufi, Ilir; Hansen, Charles; Roberts, Jonathan C.

doi:10.1177/1473871611416549

Cited by 479 publications

(366 citation statements)

References 131 publications

(90 reference statements)

Supporting

Mentioning

348

Contrasting

Unclassified

Order By: Relevance

“…Participants are shown a "standard" modulus object and are asked to change the intensity of a second object (the stimulus) until it is perceived to be equivalent to the modulus. We chose a magnitude production methodology for our experiment as the comparison judgements it requires are extremely frequent in information visualization [19]. We give additional justification in Section 4.…”

Section: Background In Psychophysicsmentioning

confidence: 99%

Perception of Visual Variables on Tiled Wall-Sized Displays for Information Visualization Applications

Bezerianos

Isenberg

2012

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

Fig. 1. Two viewers analyzing data visualizations from different viewpoints in front of a large high-resolution wall display (a). A participant conducting a trial during our first experiment (b).Abstract-We present the results of two user studies on the perception of visual variables on tiled high-resolution wall-sized displays. We contribute an understanding of, and indicators predicting how, large variations in viewing distances and viewing angles affect the accurate perception of angles, areas, and lengths. Our work, thus, helps visualization researchers with design considerations on how to create effective visualizations for these spaces. The first study showed that perception accuracy was impacted most when viewers were close to the wall but differently for each variable (Angle, Area, Length). Our second study examined the effect of perception when participants could move freely compared to when they had a static viewpoint. We found that a far but static viewpoint was as accurate but less time consuming than one that included free motion. Based on our findings, we recommend encouraging viewers to stand further back from the display when conducting perception estimation tasks. If tasks need to be conducted close to the wall display, important information should be placed directly in front of the viewer or above, and viewers should be provided with an estimation of the distortion effects predicted by our work-or encouraged to physically navigate the wall in specific ways to reduce judgement error.

show abstract

Section: Background In Psychophysicsmentioning

confidence: 99%

Perception of Visual Variables on Tiled Wall-Sized Displays for Information Visualization Applications

Bezerianos

Isenberg

2012

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

show abstract

“…The intuition to measure a subspace's quality differs significantly from earlier approaches, as outlined in Section 2. In addition, novel user interfaces and visualizations are necessary to understand and interpret multiple, partially redundant, subspaces and their different rankings [4].…”

Section: Discussion and Open Research Questionsmentioning

confidence: 99%

Subspace Nearest Neighbor Search - Problem Statement, Approaches, and Discussion

Hund

Behrisch

Färber

et al. 2015

Similarity Search and Applications

View full text Add to dashboard Cite

Abstract.Computing the similarity between objects is a central task for many applications in the field of information retrieval and data mining. For finding k-nearest neighbors, typically a ranking is computed based on a predetermined set of data dimensions and a distance function, constant over all possible queries. However, many high-dimensional feature spaces contain a large number of dimensions, many of which may contain noise, irrelevant, redundant, or contradicting information. More specifically, the relevance of dimensions may depend on the query object itself, and in general, different dimension sets (subspaces) may be appropriate for a query. Approaches for feature selection or -weighting typically provide a global subspace selection, which may not be suitable for all possibly queries. In this position paper, we frame a new research problem, called subspace nearest neighbor search, aiming at multiple querydependent subspaces for nearest neighbor search. We describe relevant problem characteristics, relate to existing approaches, and outline potential research directions.

show abstract

“…Visual Analysis for evaluation of segmentation results and comparative visualization is the topic of several recent works reviewed in [11,7]. Some works analyze the effect of segmentation parameters on the result (e.g., [14]).…”

Section: Related Workmentioning

confidence: 99%

Visual Comparison of 3D Medical Image Segmentation Algorithms Based on Statistical Shape Models

Geurts

Sakas

Kuijper

et al. 2015

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. 3D medical image segmentation is needed for diagnosis and treatment. As manual segmentation is very costly, automatic segmentation algorithms are needed. For finding best algorithms, several algorithms need to be evaluated on a set of organ instances. This is currently difficult due to dataset size and complexity. In this paper, we present a novel method for comparison and evaluation of several algorithms that automatically segment 3D medical images. It combines algorithmic data analysis with interactive data visualization. A clustering algorithm identifies regions of common quality across the segmented data set for each algorithm. The comparison identifies best algorithms per region. Interactive views show the algorithm quality. We applied our approach to a real-world cochlea dataset, which was segmented with several algorithms. Our approach allowed segmentation experts to compare algorithms on regional level and to identify best algorithms per region.

show abstract

Visual comparison for information visualization

Cited by 479 publications

References 131 publications

Perception of Visual Variables on Tiled Wall-Sized Displays for Information Visualization Applications

Perception of Visual Variables on Tiled Wall-Sized Displays for Information Visualization Applications

Subspace Nearest Neighbor Search - Problem Statement, Approaches, and Discussion

Visual Comparison of 3D Medical Image Segmentation Algorithms Based on Statistical Shape Models

Contact Info

Product

Resources

About