A Fast Pen Gesture Matching Method Based on Nonlinear Embedding
The Nearest-Neighbor (NN) rule is a widely used technique for pen gesture recognition.It is quite simple and effective, furthermore, it allow for flexible extension of newly defined classes and training samples.However, the expensive cost of computation is a key issue need to be addressed.A fast template matching method for pen gesture recognition was proposed.We embed gesture description vectors nonlinearly into a low-dimensional space.The square Euclidean distance in the embedded space can be used as the lower bound of the distance in the original space, thus most dissimilar training templates could be rejected in the embedded space.Experiment results show that our method is almost over an order of magnitude faster than the naive NN while achieving comparable recognition accuracy.Moreover, it does not rely on complex data structures or preprocessing, making it more suitable for applications that call for dynamic training data, such as user adaptive recognition.
Pen gesture Nearest neighbor Fast Matching Nonlinear embedding
Yougen Zhang Wei Deng Hanchen Song Lingda Wu
Science and Technology on Information Systems Engineering Laboratory,National University of Defense Key Laboratory, Academy of Equipment, Beijing 101416, China Science and Technology on Information Systems Engineering Laboratory,National University of Defense
国际会议
第八届图像图形技术与应用学术会议(8th Conference on Image and Graphics Technologies and Applications)(IGTA2013)
北京
英文
223-231
2013-04-02（万方平台首次上网日期，不代表论文的发表时间）