| Summary: | 碩士 === 國立臺北科技大學 === 電資碩士班 === 98 === The main purpose of this paper is to learn how to use (apply) SVM (Support Vector Machine) to design a High Recognition Rate and high efficiency multi-touch recognition system. With the advances of computer technology, the traditional data input methods, such as keyboard and mouse, have become insufficient, while the voice, camera and touch panel, the new data input methods are getting more attention nowadays. A traditional touch pad, with single-point input can only replace the traditional mouse. In these days, multi-touch panel technology is getting mature and reliable, therefore, how to identify multi-point input has become a hot research topic recently. This paper is based on SVM (support vector machine), in addition to discuss and study more additional features and needs of the SVM, to design a algorithm can recognize variety of hand gestures and highly efficient.
According to the study, the support vector machine (SVM) is a very effective tool for classification, however, during the process of SVM, the enter data has to be a fixed dimension, which will be a big problem in practice, since some data dimensions are not fixed. Therefore this paper is to study how to sort out and use the feature value when dimension of the data is not fixed, then transfer it to a fixed dimension data (here referred to as feature vectors), so it can be used as the input data for SVM. The study found that a simple sampling method, identify the effectiveness and efficiency are the best ones.
|
|---|
