Vision-based short range interaction between a personal service robot and a user |
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Authors: | Matheen Siddiqui Wei-Kai Liao Gérard Medioni |
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Affiliation: | (1) Institute for Robotics and Intelligent Systems, University of Southern California, Los Angeles, CA, USA |
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Abstract: | Interaction between a personal service robot and a human user is contingent on being aware of the posture and facial expression
of users in the home environment. In this work, we propose algorithms to robustly and efficiently track the head, facial gestures,
and the upper body movements of a user. The face processing module consists of 3D head pose estimation, modeling nonrigid
facial deformations, and expression recognition. Thus, it can detect and track the face, and classify expressions under various
poses, which is the key for human–robot interaction. For body pose tracking, we develop an efficient algorithm based on bottom-up
techniques to search in a tree-structured 2D articulated body model, and identify multiple pose candidates to represent the
state of current body configuration. We validate these face and body modules in varying experiments with different datasets,
and the experimental results are reported. The implementation of both modules can run in real-time, which meets the requirement
for real-world human–robot interaction task. These two modules have been ported onto a real robot platform by the Electronics
and Telecommunications Research Institute. |
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Keywords: | |
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