HMM-based sketch recognition system:design and optimization
基于隐性马尔可夫模型的手势识别设计和优化

Newly pen-based interaction technology requires efficient user gesture recognition and user style adaption. This paper built an HMM-based sketch recognition system and used a new method called Midpoint-Compensation in resampling phase and an improved direction coding method for optimization. The experiment shows that the sketch recognition model can recognizes user gesture efficiently meanwhile with smaller data to represent the gesture and less computation for training the model.