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Conference papers
Combined Segmentation and Recognition of Online Handwritten Diagrams with High Order Markov Random Field
Abstract : In this research we focus on the recognition of
online handwritten diagrams, which is widely applied in note
recording. Handwritten diagram is a kind of 2D language
that spans in the plane, consisting of symbols and structures.
Previous researches in the field of 2D language symbol recognition involved a complicated step such as symbol hypothesis
generation and grammar description. By building a three order
Markov random field on the stroke level, we not only labeled
strokes but stroke relationships so that we could complete
symbol grouping and symbol recognition simultaneously. The
potential function in our Markov random field is log-linear
model so that it is fully data-driven, and we trained it using
max-margin method. We tested our method on two public
handwritten diagram datasets and experiment showed that our
symbol recognition method’s performance has reached state-of-the-art.
https://hal.archives-ouvertes.fr/hal-01374389
Contributor : Harold Mouchère <>
Submitted on : Friday, September 30, 2016 - 1:21:47 PM
Last modification on : Tuesday, January 14, 2020 - 3:57:09 PM
Contributor : Harold Mouchère <>
Submitted on : Friday, September 30, 2016 - 1:21:47 PM
Last modification on : Tuesday, January 14, 2020 - 3:57:09 PM