Recognition of human gesture leads to a dynamic field that produces many various methods. The main way to improve the recognition process is to perform data fusion based on a qualification of each recognition method. The advance in data fusion gives also several solutions and the choice of a fusion method is a crucial point. The goal of this paper is to present an approach were the choice of the fusion method is driven by the constraints of the final user of data. Such constraints are expressed as bounds on indicators like confidence or accuracy. A practical experimentation illustrating this approach is presented in this paper. From a depth camera sensor, human gesture is interpreted and, fusion method is selected in accordance with the constraints of the final information consumer. This approach is illustrated in a robotic control by human gesture: outputs perform the action to be done by a NAO robot.