Interactive Lenses for Visualization: An Extended Survey

Multi‐Light Image Collections (MLICs), i.e., stacks of photos of a scene acquired with a fixed viewpoint and a varying surface illumination, provide large amounts of visual and geometric information. In this survey, we provide an up‐to‐date integrative view of MLICs as a mean to gain insight on objects through the analysis and visualization of the acquired data. After a general overview of MLICs capturing and storage, we focus on the main approaches to produce representations usable for visualization and analysis. In this context, we first discuss methods for direct exploration of the raw data. We then summarize approaches that strive to emphasize shape and material details by fusing all acquisitions in a single enhanced image. Subsequently, we focus on approaches that produce relightable images through intermediate representations. This can be done both by fitting various analytic forms of the light transform function, or by locally estimating the parameters of physically plausible models of shape and reflectance and using them for visualization and analysis. We finally review techniques that improve object understanding by using illustrative approaches to enhance relightable models, or by extracting features and derived maps. We also review how these methods are applied in several, main application domains, and what are the available tools to perform MLIC visualization and analysis. We finally point out relevant research issues, analyze research trends, and offer guidelines for practical applications.

Section: Discussionmentioning

confidence: 99%

State‐of‐the‐art in Multi‐Light Image Collections for Surface Visualization and Analysis

Pintus

Dulecha

Ciortan

et al. 2019

“…Distortion‐Based Second, distortion‐based approaches can alleviate the impact of occlusion by distorting a map, emphasizing areas and presenting more or different information than compared to the undistorted original scale of the map. A recent survey by Tominski et al [TGK*17] provides an extensive overview on the current approaches. Classical distortion‐based techniques such as the graphical Fisheye Views introduced by Sarkar and Brown [SB94] mostly employ a uniform distortion, such as a circle fading out the distortion radially around the center of focus.…”

Section: Scope Of Surgerycutsmentioning

confidence: 99%

SurgeryCuts: Embedding Additional Information in Maps without Occluding Features

Angelini

Buchmüller

Keim

et al. 2019

Visualizing contextual information to a map often comes at the expense of overplotting issues. Especially for use cases with relevant map features in the immediate vicinity of an information to add, occlusion of the relevant map context should be avoided. We present SurgeryCuts, a map manipulation technique for the creation of additional canvas area for contextual visualizations on maps. SurgeryCuts is occlusion‐free and does not shift, zoom or alter the map viewport. Instead, relevant parts of the map can be cut apart. The affected area is controlledly distorted using a parameterizable warping function fading out the map distortion depending on the distance to the cut. We define extended metrics for our approach and compare to related approaches. As well, we demonstrate the applicability of our approach at the example of tangible use cases and a comparative user study.

“…The implementation details concerning the language's interpreter do not seem to be available for comparison with our method. Tominski et al provide a recent extended survey on the generalization of a common technique in Focus+Context visualization termed the “Interactive Lens” [TGK*17]. Our design incorporates several lenses that are categorized by their survey.…”

Section: Related Workmentioning

confidence: 99%

An Interactive Visualization System for Large Sets of Phase Space Trajectories

Neuroth

Sauer

Liu

2019

We introduce a visual analysis system with GPU acceleration techniques for large sets of trajectories from complex dynamical systems. The approach is based on an interactive Boolean combination of subsets into a Focus+Context phase‐space visualization. We achieve high performance through efficient bitwise algorithms utilizing runtime generated GPU shaders and kernels. This enables a higher level of interactivity for visualizing the large multivariate trajectory data. We explain how our design meets a set of carefully considered analysis requirements, provide performance results, and demonstrate utility through case studies with many‐particle simulation data from two application areas.