Resource type
Date created
2018-06-22
Authors/Contributors
Author: Lior Bragilevsky
Author: Ivan V. Bajic
Abstract
Many software applications exist for plotting graphs of mathematical functions, yet there are none (to our knowledge) that perform the inverse operation - estimating mathematical expressions from graphs. Since plotting graphs (especially by hand) is often referred to as "sketching," we refer to the inverse operation as "de-sketching." As the number of mathematical expressions that approximate a given curve can be quite large, in this demo we restrict our attention to polynomials, and present a deep model that performs de-sketching by finding the best second-degree polynomial to fit the curve in the input image. Currently, our trained model is able to provide reasonably accurate estimates of polynomial coefficients for both synthetically-generated and hand-drawn curves.
Document
Published as
L. Bragilevsky and I. V. Bajic, "De-sketching," IEEE Multimedia Signal Processing Workshop (MMSP), Vancouver, BC, Aug. 2018.
Rights (standard)
Copyright statement
Copyright is held by the author(s).
Scholarly level
Peer reviewed?
Yes
Language
English
Member of collection
Download file | Size |
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de-sketching.pdf | 297.33 KB |