An Improved Hand Tracking System Using Pb-Hfa, Scs And Cb Model

A Real-Time Hand Gesture Detection and Recognition Using Bag-of-Features of The proposed method is a user-friendly method that easily authors (creates and controls) gesture motion according to the number of fingers. The effectiveness of the proposed motion authoring method was verified based on motion authoring simulation of an industrial robot. With rapid developments in today's robot technology, robots have been used in a wide range of fields. However, robots must become easier to use for general users in order to expand the scope of applications of intelligent robots in our everyday life. Based on this request, a number of studies are being conducted regarding new types of user-friendly and intuitive robot motion authoring that can render various motions. It described a real-time system that consists of three modules: hand detection and tracking using face subtraction, skin detection and contour comparison algorithm, posture recognition using bag features .Three important factors affect the accuracy of the system, which are the quality of the webcam in the training and testing stages, the number of the training images, and choosing number of clusters to build the cluster model.