Continuous Hand Gestures Tracking and Recognition Using The Hierarchy Hand Model

• Main Authors: Liang-Chien Chen, 陳良傑
• Other Authors: Chueh-Wei Chang
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/82w7ue

碩士 === 國立臺北科技大學 === 資訊工程系研究所 === 96 === The algorithm of hand gestures tracking and recognition using in application has two problems that effect the system. One problem is the constrain before using system, such as define of target color. The other problem is the necessity of huge image data of training learning system, which will constrain the minimum memory size. However, the principle of Human-Computer Interaction is naturally to be used, the above problems will enable the un-nature use. Hierarchy Hand Model(HHM) is a feature that can solve above problems by using hand logic. To solve the first constrain, HHM defines hand shape to use hand logic, then it is not necessary to define the target color. For the second constrain, HHM using hand logic to detect hand parameter, so that the recognition can be used by the physical models. The tracking algorithm using HHM that has a problem of performance. However, Kernel-Based object tracking has good performance and outcome when mix Mean-Shift and Particle-Filter algorithm. In preprocess, using ROI-MAP to reduce tracking region. In recognition, divide hand gestures for static gestues and continuous gestures that is the signal can easily be used in application system.