Addressing Class Distribution Issues of the Drawing vs Writing Classification in an Ink Stroke Sequence

Simple item page
dc.contributor.authorWang, Xinen_US
dc.contributor.authorBiswas, Manojen_US
dc.contributor.authorRaghupathy, Sashien_US
dc.contributor.editorMichiel van de Panne and Eric Saunden_US
dc.date.accessioned2014-01-28T17:52:47Z
dc.date.available2014-01-28T17:52:47Z
dc.date.issued2007en_US
dc.description.abstractComplicated by temporal correlations among the strokes and varying distributions of the underlying classes, the drawing/writing classification of ink strokes in a digital ink file poses interesting challenges. In this paper, we present our efforts in addressing some of the issues. First, we describe how we adjust the outputs of the neural network to a priori probabilities of new observations to produce more accurate estimates of the posterior probabilities. Second, we describe how to adapt the parameters of the HMM to new data sets. Albeit the fact that the emission probabilities of the HMM are computed indirectly from the outputs of the neural network, our modified Baum-Welch algorithm still finds the correct estimates for the HMM's parameters. We also present experimental results of our new algorithms on 6 real world data sets. The results show that our methods increase the F Measures of both the drawing and the writing classes on the more ''drawing intensive'' data sets which have stronger temporal correlations. But they do not perform well on the more ''writing intensive'' data sets.en_US
dc.description.seriesinformationEUROGRAPHICS Workshop on Sketch-Based Interfaces and Modelingen_US
dc.identifier.isbn978-3-905674-00-2en_US
dc.identifier.issn1812-3503en_US
dc.identifier.urihttps://doi.org/10.2312/SBM/SBM07/139-146en_US
dc.publisherThe Eurographics Associationen_US
dc.titleAddressing Class Distribution Issues of the Drawing vs Writing Classification in an Ink Stroke Sequenceen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
139-146.pdf
Size:
2.25 MB
Format:
Adobe Portable Document Format
Download
Collections
SBM07: Sketch Based Interfaces and Modeling 2007