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ICMLC
2005
Springer

Adaptive Online Multi-stroke Sketch Recognition Based on Hidden Markov Model

10 years 5 months ago
Adaptive Online Multi-stroke Sketch Recognition Based on Hidden Markov Model
This paper presents a novel approach for adaptive online multi-stroke sketch recognition based on Hidden Markov Model (HMM). The method views the drawing sketch as the result of a stochastic process that is governed by a hidden stochastic model and identified according to its probability of generating the output. To capture a user’s drawing habits, a composite feature combining both geometric and dynamic characteristics of sketching is defined for sketch representation. To implement the stochastic process of online multi-stroke sketch recognition, multi-stroke sketching is modeled as an HMM chain while the strokes are mapped as different HMM states. To fit the requirement of adaptive online sketch recognition, a variable state-number determining method for HMM is also proposed. The experiments prove both the effectiveness and efficiency of the proposed method.
Zhengxing Sun, Wei Jiang, Jianyong Sun
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ICMLC
Authors Zhengxing Sun, Wei Jiang, Jianyong Sun
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