Motion-based pedesvtrian recognition from a moving vehicle

This article presents the results of a detailed investigation of motion-based recognition of pedestrians. Here, the influence of the ego motion and its compensation in view of the recognition performance play a central role. Therefore, two basic approaches for the estimation of the object movement are specified, tested and evaluated. Moreover, different features for the generation of the time series are analyzed. These form the basis for the recognition of the periodicity of the human walk. The time series are used for the generation of a power density spectrum, in which the verification of the object movement is carried out. Since the quality of the evaluated spectrum and hence the robustness of the recognition depends on the duration of the measurement sequence, this correlation is carefully considered in order to define the marginal conditions. Furthermore, all variations of different walking directions are tested, as well as the distances of the object in relation to the position of the own vehicle. The obtained results show that in most cases the recognition of a moving human being is possible. This method represents an interesting possibility to increase the reliability of technical systems for recognizing of pedestrians