Classifying still faces with ultrasonic sensing

Authors:
Phillip McKerrow;Kok Kai Yoong
Affiliations:
School of Computer Science and Software Engineering, University of Wollongong, Northfields Avenue, Wollongong NSW 2522, Australia;School of Computer Science and Software Engineering, University of Wollongong, Northfields Avenue, Wollongong NSW 2522, Australia
Venue:
Robotics and Autonomous Systems
Year:
2007

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Abstract

The echo of a chirp of ultrasonic energy from an object contains information about the geometry of that object: the relative depth of its surfaces and the approximate area of those surfaces. A human face has complex geometry that produces a distinctive echo. In this paper, we report the initial research into whether there is sufficient information in the echo to recognize a still face. Potential features for classification are identified using a facial model. The classification results for 10 faces encourage future research with a larger number of faces and with moving faces.