i-ManGoeS

HuMan activity(Go) System (i-ManGoeS) using digital camera is important in library. Human Human activity system is an essential area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on edge detection from a digital camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic gestures. The training phase creates several models related to the number of clustered gestures by fuzzy logic. The contribution of this paper is to perform activity recognition employing features based on a small number of informative gestures, extracted independently from each activity instance. At the end this paper give some preliminary results and conclude on the effectiveness of this approach. i-ManGoes is an application software that use computer vision technique to classify the children activity and satisfaction base on gesture. Computer vision is a technology that gathers information from the images captured from a real world application. Next, the image are segmented to separate object and backgroud. Then, the features are extracted from the object. Finally fuzzy learning algorithm will formulate the object features to classify the children activity and satisfaction.