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.
25 Citations
21 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 non-transitory 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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Specification