Automated Gesture Recognition

• US 20080192005A1
• Filed: 10/19/2005
• Published: 08/14/2008
• Est. Priority Date: 10/20/2004
• Status: Abandoned Application

• Current Assignee: Glasgow School of Art
• Original Assignee: Glasgow School of Art
• Inventors: Anderson, Paul, Payne, John, Kenny, Tom, Elgoyhen, Jocelyn, Keir, Paul
• Application Number:
  US11/577,694
• Publication Number:
  US 20080192005A1
• Time in Patent Office: Days
• US Class Current: 345/158
• CPC Class Codes: G06F 2203/0331 Finger worn pointing device
• CPC Class Codes: G06F 3/014 Hand-worn input/output arrangements, e.g. data gloves
• 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: G06F 3/0346 with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16

Abstract

A gesture recognition engine and method provides for recognition of gestures comprising movement of an object. Input data is received related to a succession of positions, velocities, accelerations and/or orientations of the at least one object, as a function of time, which input defines a trajectory of the at least one object. Vector analysis is performed on the trajectory data to determine a number N of vectors making up the object trajectory, each vector having a length and a direction relative to a previous or subsequent vector or to an absolute reference frame, the vectors defining an input gesture signature. The input gesture signature is compared, on a vector by vector basis, with corresponding vectors of a succession of library gestures stored in a database, to identify a library gesture that corresponds with the trajectory of the at least one object.

Claims

1. A gesture recognition method comprising the steps of:

a) receiving input data related to a succession of positions, velocities, accelerations and/or orientations of at least one object, as a function of time, which input is representative of a trajectory of the at least one object;

b) performing a vector analysis on the trajectory data to determine a number N of vectors making up the object trajectory, each vector having a length and a direction relative to a previous or subsequent vector or to an absolute reference frame, the vectors defining a gesture signature;

c) on a vector by vector basis, comparing the object trajectory with a plurality of library gestures stored in a database, each library gesture also being defined by a succession of such vectors; and

d) identifying a library gesture that corresponds with the trajectory of the at least one object.

2. The method of claim 1 in which step a) further includes determining said received input data from the output of at least one sensor positioned on the object.

3. The method of claim 1 in which step a) further includes determining said received input data from a series of images of the object.

4. The method of claim 1 further including the step of identifying a start and/or end of the received input data sequence by detecting a trigger input from manual activation of any type of electronic, electromechanical, optoelectronic or other physical switching device.

5. The method of claim 1 further including the step of identifying a start and/or end of the received input data sequence by continuously monitoring the input data for a pattern or sequence corresponding to a predetermined trajectory of the object.

6. The method of claim 1 in which, step a) is preceded by an operation comprising determining a configuration of input device to establish a number and type of input data streams corresponding to one or more of:

position data, velocity data, acceleration data, number of translation axes, number of rotation axes, and absolute or relative data type.

7. The method of claim 1 in which the input data is pre-processed to remove DC offsets and/or low frequency components.

8. The method of claim 1 in which the input data is pre-processed by low pass filtering to smooth the input data.

9. The method of claim 1 in which the input data is pre-processed to convert all inputs to data representing velocity of the sensor as a function of time.

10. The method of claim 1 in which the input data is pre-processed to convert it to values relative to one or more reference frames.

11. The method of claim 1 in which the input data is pre-processed to generate a predetermined number of data samples over a gesture time period or gesture trajectory length.

12. The method of claim 1 in which step b) includes determining, for each vector except the first, a direction relative to a preceding vector.

13. The method of claim 1 in which step b) includes determining, for each vector except the first two, a direction relative to a plane defined by the preceding two vectors.

14. The method of claim 1 in which step b) includes determining, for at least one of the vectors, a direction relative to a predetermined reference frame.

15. The method of claim 1 in which step b) includes determining, for each successive vector pair, a ratio R of respective vector lengths, l_n+1/l_n;

an azimuth angle between the vectors; and

a zenith angle of the second vector of the pair relative to the plane defined by the preceding two vectors.

16. The method of claim 1 in which step b) includes determining, for the first vector pair, a ratio R of respective vector lengths, l₂/l₁, and an angle between the vectors.

17. The method of claim 15 in which step c) comprises comparing each of the vector pair length ratios R with a corresponding vector pair length ratio of a library gesture.

18. The method of claim 15 in which step c) comprises comparing each of the azimuth angles between the vectors with a corresponding angle of a library gesture.

19. The method of claim 15 in which step c) comprises comparing each of the zenith angles with a corresponding angle from the library gesture.

20. The method of claim 1 in which step d) comprises determining the correspondence of the input gesture signature of the at least one object with a library gesture signature when a threshold degree of match is reached.

21. The method of claim 1 in which step d) comprises determining the correspondence of the input gesture signature of the at least one object with a library gesture signature according to a best match criteria, against some or all of the library gestures in the database.

22. The method of claim 1 in which step d) comprises determining the correspondence of the trajectory of the at least one object with a library gesture taking into account a learned user variability.

23. The method of claim 1 in which the library gestures stored in a database includes standard pre-determined gestures and user-defined gestures each defined in terms of a gesture signature.

24. The method of claim 1 further including the step of performing a calibration routine on an input data sequence corresponding to a predetermined library gesture in the database.

25. The method of claim 1 further including the step of rendering an image of a hand based on the received input data.

26. A gesture recognition engine comprising:

an input for receiving input data related to a succession of positions, velocities, accelerations and/or orientations of at least one object, as a function of time, which input defines a trajectory of the at least one object;

a gesture analysis process module for performing a vector analysis on the trajectory data to determine a number N of vectors making up the object trajectory, each vector having a length and a direction relative to a previous or subsequent vector or to an absolute reference frame, the vectors defining a gesture signature; and

a gesture comparator module for comparing, on a vector by vector basis, the object trajectory with a plurality of library gestures stored in a database, each library gesture also being defined by a succession of such vectors and identifying a library gesture that corresponds with the trajectory of the at least one object.