利用Kinect之手寫英文字母及數字辨識

Abstract

人機互動在近年來是十分熱門的研究領域，而手勢辨識提供了更自然的溝通方式，是人機互動相當重要的部份。手寫辨識也是屬於手勢辨識的一部份，它提供了人機互動中輸入字母的替代方案。在本篇論文中，我們做出手寫辨識系統，讓使用者不需要傳統的輸入設備像是鍵盤和滑鼠就能夠輸入數字及英文字母。 在人機互動中對於手寫數字和英文字母需要即時的辨識並且對準確率要求比較高。因此為了提升辨識的準確率，我們提出了一種新的特徵演算法，此特徵演算法包含了書寫軌跡的時間性和空間性，並經由支援向量機和隨機決策森林進行辨識。最後我們也透過實驗證明本篇論文所提出的方法能夠即時的辨識手寫數字及英文字母並擁有相當高的精準度。

Human-computer interaction (HCI) has been a popular research field recently. Hand gesture recognition is an important part of HCI that provides a natural way of communication. Handwritten recognition is a part of hand gesture recognition that provides an alternative method to input characters. In this thesis, we propose a handwritten recognition system to input English characters and digits without using traditional input devices such as keyboards and mice. Accuracy and real time processing are highly desired in the handwritten digit and character recognition of HCI. In order to improve the accuracy, we suggest a new feature extracting algorithm which contains the temporal and spatial information of hand writing paths. Furthermore, we use support vector machines and random forests to carry out feature classification. Experimental results show that the proposed method has a very high accuracy in the handwritten digit and character recognition in real time.