Abstract:
Knowledge of calibration, that defines the location
of sensors relative to each other, and registration, that relates
sensor response due to the same physical phenomena, are
essential in order to be able to fuse information from multiple
sensors. In this paper, a Mutual Information (MI) based
approach for automatic sensor registration and calibration is
presented. Unsupervised learning of a nonparametric sensing
model by maximizing mutual information between signal streams
is used to relate information from different sensors, allowing
unknown sensor registration and calibration to be determined.
Experiments conducted in an office environment are used to
illustrate the effectiveness of the proposed technique. Two laser
sensors are used to capture people mobbing in an arbitrarily
manner in the environment and MI from a number of attributes
of the motion are used for relating the signal streams from the
sensors. Thus the sensor registration and calibration is achieved
without using artificial patterns or pre-specified motions.
