Motion pattern classification and gesture recognition
First Claim
1. A method performed by one or more computers, comprising:
- receiving a plurality of motion features, each of the motion features including a respective time series of motion vectors and a first label or a second label;
determining a respective distance between each pair of the motion features that includes a first motion feature having the first label and a second motion feature having the second label;
clustering the motion features into one or more motion clusters based on the distance and a quality threshold, the quality threshold being determined based at least in part on a smallest distance between a motion feature having the first label and a motion feature having the second label; and
representing each of the one or more motion clusters using a motion pattern for recognizing a gesture on a mobile device, the motion pattern including a time series of calculated motion vectors.
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Accused Products
Abstract
Methods, program products, and systems for gesture classification and recognition are disclosed. In general, in one aspect, a system can determine multiple motion patterns for a same user action (e.g., picking up a mobile device from a table) from empirical training data. The system can collect the training data from one or more mobile devices. The training data can include multiple series of motion sensor readings for a specified gesture. Each series of motion sensor readings can correspond to a particular way a user performs the gesture. Using clustering techniques, the system can extract one or more motion patterns from the training data. The system can send the motion patterns to mobile devices as prototypes for gesture recognition.
24 Citations
36 Claims
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1. A method performed by one or more computers, comprising:
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receiving a plurality of motion features, each of the motion features including a respective time series of motion vectors and a first label or a second label; determining a respective distance between each pair of the motion features that includes a first motion feature having the first label and a second motion feature having the second label; clustering the motion features into one or more motion clusters based on the distance and a quality threshold, the quality threshold being determined based at least in part on a smallest distance between a motion feature having the first label and a motion feature having the second label; and representing each of the one or more motion clusters using a motion pattern for recognizing a gesture on a mobile device, the motion pattern including a time series of calculated motion vectors. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A non-transitory storage device storing a computer program product configured to cause one or more computers to perform operations comprising:
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receiving a plurality of motion features, each of the motion features including a respective time series of motion vectors and being associated with a first label or a second label; determining a respective distance between each pair of the motion features that includes a first motion feature having the first label and a second motion feature having the second label; clustering the motion features into one or more motion clusters based on the distance and a quality threshold, the quality threshold being determined based at least in part on a smallest distance between a motion feature having the first label and a motion feature having the second label; and representing each of the one or more motion clusters using a motion pattern for recognizing a gesture on a mobile device, the motion pattern including a time series of calculated motion vectors. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A system, comprising:
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one or more computers; a non-transitory storage device storing instructions configured cause the one or more computers to perform operations comprising; receiving a plurality of motion features, each of the motion features including a respective time series of motion vectors and a first label or a second label; determining a respective distance between each pair of the motion features that includes a first motion feature having the first label and a second motion feature having the second label; clustering the motion features into one or more motion clusters based on the distance and a quality threshold, the quality threshold being determined based at least in part on a smallest distance between a motion feature having the first label and a motion feature having the second label; and representing each of the one or more motion clusters using a motion pattern for recognizing a gesture on a mobile device, the motion pattern including a time series of calculated motion vectors. - View Dependent Claims (26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
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Specification