Sketch-based Interfaces: Exploiting Spatio-temporal Context for Automatic Stroke Grouping

Authors:

Lutz Dickmann, Tobias Lensing, Robert Porzel, Rainer Malaka, and Christoph Lischka

Summary:

Goal: Grouping strokes in sketches based on spatio temporal data.

feature list:

- proximity, time between strokes, duration of the stroke, horizontal and vertical velocity.

- short term memory - using the features

- SVM and echo state networks.

ESN - neural network technique.

FNN - no memory

RNN - memory but convergence not gauranteed.

ESN - kind of linear combination of many RNN. (read more about this)

tested on the naive landscape scenes and hatching and arrows.

Performance score was based on precision and recall analysis.

Discussion:

What is the significance of the vertical and horizontal velocity of the stroke?

Example based automatic font generation

Authors :

Rapee Suveeranont

Takeo Igarashi

similar work: http://www.pilothandwriting.com/en/

Summary:

Goal: editing and creating a new font with font editor is difficult. correcting spline requires expertize. So reduce the work in generating a font.

Steps to create a font:

- sketch the alphabet sample with pen.

- overlay the alphabet skeleton to correct the sample.

- correct the sample(also called skin) using the overlaid skeleton.

Blending/ modifying the font.

- using various properties the skin/ sample can be modified.

- transform (shear, shrink...) the skeleton to change the skin and see the change in the UI.

Algorithm:

Once the sample alphabet is drawn by the user. The application fits the simplest skeleton to the skin drawn. (topological problems - Q). After fitting the skeleton, the system automatically corrects the skin based on the skeleton.

While blending, 2 weights are generated - one for the skeleton and one for the skin. the font is then mapped to the nearest font skin in the available database.

results:

- generating skeleton was fairly accurate.

- generating skin gave mixed results

- constraints due the linear morphing from the existing font.

- user study with 3 users and 3 trials for each.

- font generation took lesser time with each iteration

Discussion:

interesting technique. When the user gives a sketch, why match it or morph it to an existing font.