Invention Grant
- Patent Title: Machine-learning based tap detection
- Patent Title (中): 基于机器学习的抽头检测
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Application No.: US14340455Application Date: 2014-07-24
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Publication No.: US09235278B1Publication Date: 2016-01-12
- Inventor: Peter Cheng , Steven Scott Noble , Matthew Paul Bell , Yi Ding , Stephen Michael Polansky , Alexander Li Honda
- Applicant: Amazon Technologies, Inc.
- Applicant Address: US NV Reno
- Assignee: Amazon Technologies, Inc.
- Current Assignee: Amazon Technologies, Inc.
- Current Assignee Address: US NV Reno
- Agency: Novak Druce Connolly Bove + Quigg LLP
- Main IPC: G06F3/045
- IPC: G06F3/045 ; G06F3/038 ; G06F3/0354 ; G06F3/0346 ; G06K9/00 ; G06F3/0487

Abstract:
An electronic device can be configured to enable a user to provide input via a tap of the device without the use of touch sensors (e.g., resistive, capacitive, ultrasonic or other acoustic, infrared or other optical, or piezoelectric touch technologies) and/or mechanical switches. Such a device can include other sensors, including inertial sensors (e.g., accelerometers, gyroscopes, or a combination thereof), microphones, proximity sensors, ambient light sensors, and/or cameras, among others, that can be used to capture respective sensor data. Feature values with respect to the respective sensor data can be extracted, and the feature values can be analyzed using machine learning to determine when the user has tapped on the electronic device. Detection of a single tap or multiple taps performed on the electronic device can be utilized to control the device.
Public/Granted literature
- US20160026261A1 MACHINE-LEARNING BASED TAP DETECTION Public/Granted day:2016-01-28
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