Identifying and segmenting human-motion for mobile robot navigation using alignment errors

This paper presents a new human-motion identification and segmentation algorithm, for mobile robot platforms. The algorithm is based on computing the alignment error between pairs of object images acquired from a moving platform. Pairs of images generating relatively small alignment errors are used to estimate the fundamental frequency of the object´s motion. A decision criterion is then used to test the significance of the estimated frequency and to classify the object´s motion. To verify the validity of the proposed approach, experimental results are shown on different classes of objects