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首页> 外文会议>International Conference on Pattern Recognition Applications and Methods >Time-segmentation- and Position-free Recognition from Video of Air-drawn Gestures and Characters
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Time-segmentation- and Position-free Recognition from Video of Air-drawn Gestures and Characters

机译：从空气绘制手势和字符的视频的时间分割 - 无定位识别

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We report on the recognition from video streams of isolated alphabetic characters and connected cursive textual characters, such as alphabetic, hiragana a kanji characters, drawn in the air. This topic involves a number of difficult problems in computer vision, such as the segmentation and recognition of complex motion from video. We utilize an algorithm called time-space continuous dynamic programming (TSCDP) that can realize both time- and location-free (spotting) recognition. Spotting means that prior segmentation of input video is not required. Each of the reference (model) characters used is represented by a single stroke composed of pixels. We conducted two experiments involving the recognition of 26 isolated alphabetic characters and 23 Japanese hiragana and kanji air-drawn characters. Moreover we conducted gesture recognition experiments based on TSCDP and showed that TSCDP was free from many restrictions imposed upon conventional methods.
机译：我们报告了孤立字母字符的视频流和连接的草书文本字符的识别，例如字母，平假名A kanji字符，在空中绘制。本主题涉及计算机愿景中的许多困难问题，例如来自视频的复杂运动的分割和识别。我们利用一种称为时空连续动态编程（TSCDP）的算法，可以实现无时间和地点（发现）识别。发现意味着不需要输入视频的先前分割。所使用的每个参考（模型）字符由由像素组成的单个笔划表示。我们进行了两项实验，涉及26个孤立的字母字符和23个日本平原和Kanji空气绘制的人物。此外，我们进行了基于TSCDP的手势识别实验，并显示TSCDP没有对常规方法施加的许多限制。

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