Identifying and Segmenting Human-Motion for Mobile Robot Navigation using alignment errors

Abstract

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.