A panoramic vision system for human-robot interaction

We have proposed a new approach for solving a fundamental issue in HRI, that is, how to properly detect and identify people in everyday environments since some conditions might make it a difficult task. For that, fisheye cameras are used since they provide panoramic vision and one or two of them allow to cover the whole workspace. A modified background maintenance approach was developed for fast, robust motion detection; while person identification for interaction is dealt with Viola-Jones classifier, although, instead of searching in the whole image, its input is only composed of the detected moving elements. Moreover, in order to avoid restricting the system autonomy by requiring the person has to face the system any time, once a person is identified as a target for interaction, they are tracked by using another designed method. We have also carried out an implementation of the proposed approach and a comparative experiment to assess its feasibility.