Head Gesture Recognition System Using Adaboost Algorithm with Obstacle Detection

Head gesture recognition is the challenging task of research in the computer vision, mainly for the purpose of head gesture recognition of handicapped peoples using intelligent wheelchair or for the security purpose and human computer interaction. In this paper, an attempt is made to propose a system to recognize head gesture in real time from the video sequences using adaboost algorithm. The proposed system is based on a sequence of four main stages: data acquisition that is image capturing, pre processing means filtering, feature extraction that is rectangular features and a parallel stage with a cascade of classifiers design and classification. Various experiments were performed and the results demonstrate that, the system can successfully recognize head gestures using adaboost algorithm. The gesture recognition from the video sequences is one of the most important challenges in the computer vision. It offers to the system, the ability to identify, recognize and interpret the human head gestures in order to control some devices.