In order to improve the link between an operator and its machine, some human oriented communication systems are now using natural languages like speech or gesture. The goal of this paper is to present a gesture recognition system based on the fusion of measurements issued from different kind of sources. It is necessary to have some sensors that are able to capture at least the position and the orientation of the hand such as Dataglove and a video camera. Datagloge gives a measure of the hand posture and a video camera gives a measure of the general arm gesture which represents the physical and spatial properties of the gesture, and based on the 2D skeleton representation of the arm. The measurements used are partially complementary and partially redundant. The application is distributed on intelligent cooperating sensors. The paper presents the measurement of the hand and the arm gestures, the fusion processes, and the implementation solution.
Human is able to exchange information smoothly using voice under different situations such as noisy environment in a crowd and with the existence of plural speakers. We are able to detect the position of a source sound in 3D space, extract a particular sound from mixed sounds, and recognize who is talking. By realizing this mechanism with a computer, new applications will be presented for recording a sound with high quality by reducing noise, presenting a clarified sound, and realizing a microphone-free speech recognition by extracting particular sound. The paper will introduce a realtime detection and identification of particular speaker in noisy environment using a microphone array based on the location of a speaker and the individual voice characteristics. The study will be applied to develop an adaptive auditory system of a mobile robot which collaborates with a factory worker.
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