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Remote Drawing Technology Based on Motion Trajectories Analysis
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 Title & Authors
Remote Drawing Technology Based on Motion Trajectories Analysis
Leem, Seung-min; Jeong, Hyeon-seok; Kim, Sung-young;
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In this paper, we suggest new technology that can draw characters at a long distance by tracking a hand and analysing the trajectories of hand positions. It`s difficult to recognize the shape of a character without discriminating effective strokes from all drawing strokes. We detect end points from input trajectories of a syllable with camera system and localize strokes by using detected end points. Then we classify the patterns of the extracted strokes into eight classes and finally into two categories of stroke that is part of syllable and not. We only draw the strokes that are parts of syllable and can display a character. We can get 88.3% in classification accuracy of stroke patterns and 91.1% in stroke type classification.
Electric White-Board;End Points Detection;Stroke Extraction;Stroke Type Classification;Virtual Drawing;Trajectories of hand positions;
 Cited by
Bai, Y., Park, S. Y., Kim, Y. S., Jeong, I. G., Ok, S. Y., & Lee, E. J. (2011). Hand Tracking and Hand Gesture Recognition for Human Computer Interaction. Journal of Korea Multimedia Society, 14(2), 182-193.. crossref(new window)

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