Ultrasonic Doppler System and Method for Gesture Recognition

• US 20100202656A1
• Filed: 02/09/2009
• Published: 08/12/2010
• Est. Priority Date: 02/09/2009
• Status: Abandoned Application

• Current Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Inventors: Ramakrishnan, Bhiksha Raj, Kalgaonkar, Kaustubh
• Application Number:
  US12/367,720
• Publication Number:
  US 20100202656A1
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G01S 15/58 Velocity or trajectory determination systems; Sense-of-movement determination systems velocity measurement in imaging systems G01S15/8979
• CPC Class Codes: G01S 7/539 using analysis of echo signal for target characterisation; Target signature; Target cross-section
• CPC Class Codes: G01S 7/54 with receivers spaced apart
• CPC Class Codes: G06F 18/24155 Bayesian classification
• CPC Class Codes: G06F 2218/08 Feature extraction
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16

Abstract

A method and system recognizes an unknown gesture by directing an ultrasonic signal at an object making an unknown gestures. A set of Doppler signals are acquired of the ultrasonic signal after reflection by the object. Doppler features are extracted from the reflected Doppler signal, and the Doppler features are classified using a set of Doppler models storing the Doppler features and identities of known gestures to recognize and identify the unknown gesture, wherein there is one Doppler model for each known gesture.

Claims

1. A method for recognizing an unknown gesture, comprising the steps of:

directing an ultrasonic signal at an object making an unknown gestures;

acquiring a set of Doppler signals of the ultrasonic signal after reflection by the object;

extracting Doppler features from the reflected Doppler signal; and

classifying the Doppler features using a set of Doppler models storing the Doppler features and identities of known gestures to recognize and identify the unknown gesture, wherein there is one Doppler model for each known gesture.

2. The method of claim 1, wherein the object is a hand.

3. The method of claim 1, in which the set of receivers include a left, center and right receiver arranged coplanar in an XY plane, and the transmitter is displaced along a Z-axis and centimeters behind the XY plane.

4. The method of claim 1, wherein the transmitter is in-line with an orthocenter of a triangle formed by the three receivers.

5. The method of claim 1, wherein the ultrasonic signal has a frequency of 40 kHz oscillator, with a 3 db bandwidth of about 4 kHz.

6. The method of claim 1, wherein the ultrasonic signal has a beamwidth of about 60°

.

7. The method of claim 1, wherein the ultrasonic signal has a frequency f, the object has a velocity v, with respect to the transmitter, and a frequency the Doppler signal is

f=(v_s+v)(v_s−

v)<sup>−

1</sup>f,

were v_s is a velocity of the ultrasonic signal in a medium.

8. The method of claim 7, wherein each reflected signal is modeled as

9. The method of claim 1, wherein the features are cepstral coefficients.

10. The method of claim 9, further comprising:

combining the ceptral coefficients into a vector v.

11. The method of claim 9, further comprising:

decorrelating the vector v using principal component analysis.

12. The method of claim 1, wherein the classifying uses a Bayesian classifier.

13. The method of claim 12, wherein a distribution of the vectors is modeled by a set of Gaussian mixture models (GMM), one for each receiver.

14. System for recognizing an unknown gesture, comprising:

an ultrasonic transmitter configured to direct an ultrasonic signal at an object making an unknown gestures;

a set of ultrasonic receivers configured to acquiring a set of Doppler signals of the ultrasonic signal after reflection by the object;

means for extracting Doppler features from the reflected Doppler signal; and

means for classifying the Doppler features using a set of Doppler models storing the Doppler features and identities of known gestures to recognize and identify the unknown gesture, wherein there is one Doppler model for each known gesture.