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Recently convolutional neural networks (CNN) have demonstrated remarkable performance in various classification problems. In this paper, we also introduce CNN into in-air handwritten Chinese character recognition (IAHCCR) and propose new directional feature maps, named bend directional feature maps. Then we integrate the combination of various types of directional feature maps with the CNN and obtain...
With the advance of 3-dimensional sensing devices, the in-air handwriting, as a more natural way for human and computer interaction, is being developed by the UCAS-CVMT Lab. Compared with the conventional handwritten Chinese characters generated by touching, it is more challenging to accurately recognize them due to unconstrained one-stroke writing style. This paper presents two recognizers to address...
The in-air handwriting is a natural and promising humancomputer interaction way. Compared with handwritten Chinese characters on touch screen, the in-air handwritten Chinese characters have their unique characteristics, e.g., each character is always written in a single stroke. In this paper, we propose a high-order directional feature for recognizing in-air handwritten Chinese characters. The proposed...
The in-air handwriting is a natural and useful way for human-computer interaction. Yet, to our knowledge, few work has been done for the in-air handwritten Chinese character recognition (IAHCCR). In this paper, we present a multi-stage recognizer to address the problem of IAHCCR. The proposed methods can also deal with the classical handwritten Chinese character recognition (HCCR). We find that the...
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