GESTURE CATALOGING AND RECOGNITION
First Claim
1. A method for gesture recognition, comprising:
- a) receiving sample motion data from one or more sensors associated with a control device wherein the motion data is related to movement of the control device;
b) computing an energy value from the motion data and a baseline value for the motion data;
c) updating the baseline value based on the energy value if the energy value is less than a calm energy threshold;
d) adjusting the sample motion data based on the updated baseline value;
e) calculating a local variance of the sample motion data over a predetermined number of local variance samples;
f) beginning recording one or more values of the sample motion data for a gesture if the local variance scalar value is greater than a threshold for beginning recording;
g) calculating an average local variance scalar value using the one or more values of the sample motion data for a gesture; and
h) stopping the recording of the one or more values of the sample motion data for a gesture if the local variance scalar value is less than a threshold for stopping recording.
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Accused Products
Abstract
Methods and apparatus for cataloging and recognizing gestures are disclosed. A gesture may be detected using sample motion data. An energy value and a baseline value may be computed. The baseline value may be updated if the energy value is below a calm energy threshold. The sample motion data may be adjusted based on the updated baseline value. A local variance may be calculated over a predetermined number of samples. Sample motion data values may be recorded if the local variance exceeds a threshold. Sample motion data recording may stop if a local variance scalar value falls below a drop threshold. Input Gestures may be recognized by computing a total variance for sample values in an Input Gesture; calculating a figure of merit using sample values from the Input Gesture and one or more Catalog Gestures; and determining whether the Input Gesture matches a Catalog Gesture from the figure of merit.
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Citations
33 Claims
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1. A method for gesture recognition, comprising:
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a) receiving sample motion data from one or more sensors associated with a control device wherein the motion data is related to movement of the control device; b) computing an energy value from the motion data and a baseline value for the motion data; c) updating the baseline value based on the energy value if the energy value is less than a calm energy threshold; d) adjusting the sample motion data based on the updated baseline value; e) calculating a local variance of the sample motion data over a predetermined number of local variance samples; f) beginning recording one or more values of the sample motion data for a gesture if the local variance scalar value is greater than a threshold for beginning recording; g) calculating an average local variance scalar value using the one or more values of the sample motion data for a gesture; and h) stopping the recording of the one or more values of the sample motion data for a gesture if the local variance scalar value is less than a threshold for stopping recording. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. An apparatus for gesture recognition comprising:
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a control device; a processor operable to execute a program of a method for gesture recognition, wherein the method comprising; receiving sample motion data from one or more sensors associated with the control device wherein the motion data is related to movement of the control device; computing an energy value from the motion data and a baseline value for the motion data; updating the baseline value based on the energy value if the energy value is less than a calm energy threshold; adjusting the sample motion data based on the updated baseline value; calculating a local variance if the sample motion data over a predetermined number of local variance samples; beginning recording one or more values of the sample motion data for a gesture if the local variance scalar value is greater than a start threshold; calculating an average local variance scalar value using the one or more values of the sample motion data for a gesture; and stopping the recording of the one or more values of the sample motion data for a gesture if the local variance scalar value is less than a stop threshold. - View Dependent Claims (20)
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21. A computer readable storage medium having computer readable instructions embodied therein, the computer readable instructions being configured to implement, when executed, a method for gesture recognition, the method comprising:
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receiving sample motion data from a sensor associated with a control device wherein the motion data is related to movement of the control device; computing an energy value from the motion data and a baseline value for the motion data; updating the baseline value based on the energy value if the energy value is less than a calm energy threshold; adjusting the sample motion data based on the updated baseline value; calculating a local variance if the sample motion data over a predetermined number of local variance samples; beginning recording one or more values of the sample motion data for a gesture if the local variance scalar value is greater than a start threshold; calculating an average local variance scalar value using the one or more values of the sample motion data for a gesture; and stopping the recording of the one or more values of the sample motion data for a gesture if the local variance scalar value is less than a stop threshold.
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22. In a system having a control device and a processor coupled to the control device, a gesture recognition method comprising:
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a) computing with the processor a total variance for sample values in an input gesture including a plurality of sample values of sample motion data from one or more sensors associated with the control device wherein the motion data is related to movement of the control device; b) calculating a figure of merit using the sample values in the gesture and sample values in one or more catalog gestures, wherein the figure of merit measures how well the samples in the input gesture match samples in the catalog gesture; c) determining whether an input gesture matches one of the one or more catalog gesture based on the figure of merit; and d) changing a state of the system if it is determined that the input gesture matches the one of the one or more catalog gestures. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30, 31)
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32. An apparatus for gesture recognition comprising:
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a control device; a processor operable to execute a program of a method for gesture recognition, wherein the method comprising; a) computing a total variance for sample values in an input gesture including a plurality of sample values of sample motion data from one or more sensors associated with the control device wherein the motion data is related to movement of the control device; b) calculating a figure of merit using the sample values in the gesture and sample values in one or more catalog gestures, wherein the figure of merit measures how well the samples in the input gesture match samples in the catalog gesture; c) determining whether an input gesture matches one of the one or more catalog gesture based on the figure of merit; and d) changing a state of the apparatus if it is determined that the input gesture matches the one of the one or more catalog gestures.
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33. A computer readable storage medium having computer readable instructions embodied therein, the computer readable instructions being configured to implement, when executed, a method for gesture recognition, the method comprising:
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a) computing a total variance for sample values in an input gesture including a plurality of sample values of sample motion data from one or more sensors associated with a control device wherein the motion data is related to movement of the control device; b) calculating a figure of merit using the sample values in the gesture and sample values in one or more catalog gestures, wherein the figure of merit measures how well the samples in the input gesture match samples in the catalog gesture; and c) determining whether an input gesture matches one of the one or more catalog gesture based on the figure of merit.
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Specification