Multi-Initialized States Referred Work Parameter Calibration for Gaze Tracking Human-Robot Interaction

摘要

In order to adaptively calibrate the work parameters in the infrared-TV based eye gaze tracking Human-Robot Interaction (HRI) system, a kind of gaze direction sensing model has been provided for detecting the eye gaze identified parameters. We paid more attention to situations where the user's head was in a different position to the interaction interface. Furthermore, the algorithm for automatically correcting work parameters of the system has also been put up by defining certain initial reference system states and analysing the historical information of the interaction between a user and the system. Moreover, considering some application cases and factors, and relying on minimum error rate Bayesian decision-making theory, a mechanism for identifying system state and adaptively calibrating parameters has been proposed. Finally, some experiments have been done with the established system and the results suggest that the proposed mechanism and algorithm can identify the system work state in multi-situations, and can automatically correct the work parameters to meet the demands of a gaze tracking HRI system.