Image composition extracts the content of interest (COI) from a source image and blends it into a target image to generate a new image. In the majority of existing works, the COI is manually extracted and then overlaid on ...

Palette-based image decomposition has attracted increasing attention in recent years. A specific class of approaches have been proposed basing on the RGB-space geometry, which manage to construct convex hulls whose vertices ...

We present an incremental Voronoi vertex labelling algorithm for approximating contours, medial axes and dominant points (high curvature points) from 2D point sets. Though there exist many number of algorithms for ...

Analyzing complex data is a non-linear process that alternates between identifying discrete facts and developing overall assessments and conclusions. In addition, data analysis rarely occurs in solitude; multiple collaborators ...

In this paper, we present a real-time technique to visualize large-scale adaptive height fields with C1-continuous surface reconstruction. Grid-based shallow water simulation is an indispensable tool for interactive flood ...

Digital acquisition and processing techniques are changing the way neuroscience investigation is carried out. Emerging applications range from statistical analysis on image stacks to complex connectomics visual analysis ...

Cognitive biases are systematic errors in judgment due to an over-reliance on rule-of-thumb heuristics. Recent research suggests that cognitive biases, like numerical anchoring, transfers to visual analytics in the form ...

Pan and zoom are basic yet powerful interaction techniques for exploring large datasets. However, existing zoomable UI toolkits such as Pad++ and ZVTM do not provide the backend database support and data-driven primitives ...

We propose a method for the data-driven inference of temporal evolutions of physical functions with deep learning. More specifically, we target fluid flow problems, and we propose a novel LSTM-based approach to predict the ...