Digit-writing hand gesture recognition by hand-held camera motion analysis

J. Hao, T. Shibata
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引用次数: 6

Abstract

A camera motion detection and analysis algorithm applicable to hand-held devices, such as mobile phones, has been developed and applied to digit-writing gesture recognition. The writing stroke is recorded from an image sequence taken by a moving camera. The automatic speed adaptation capability developed in the motion detection system has enabled very robust writing stroke detection. As a result, the temporal stroke distortion due to irregular writing speed has been eliminated. Since both the direction and magnitude of motion is detected at each instant, the writing stroke is correctly reconstructed by integrating the results. For this reason, feature vector for each digit character was constructed by connecting feature distribution in each direction. As a result, handwriting gesture recognition is achieved by simple template matching. The system performance has been evaluated by digit-writing gesture recognition with irregular writing speed, different users, or cursive writing. Preliminary experiments on hand-writing Chinese character recognition have also been attempted and the potentiality of the algorithm for more complicated gesture patterns has been tested.
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手持式相机运动分析的数字书写手势识别
开发了一种适用于手持设备(如移动电话)的摄像机运动检测与分析算法,并将其应用于数字书写手势识别。书写笔划是从移动摄像机拍摄的图像序列中记录下来的。在运动检测系统中开发的自动速度适应能力使书写笔划检测非常鲁棒。因此,消除了由于书写速度不规则而造成的时间笔画失真。由于在每个瞬间都检测到运动的方向和大小,因此通过积分结果可以正确地重建书写笔划。为此,通过连接各个方向的特征分布,构建每个数字字符的特征向量。因此,手写手势识别是通过简单的模板匹配实现的。通过不规则书写速度、不同用户或草书书写的数字书写手势识别对系统性能进行了评估。手写汉字识别的初步实验也进行了尝试,并测试了该算法在更复杂手势模式下的潜力。
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