Abstract:
Systems and methods for human hand gesture recognition through a training mode and a recognition mode are disclosed. In the training mode, a user can move a handheld device with a hand gesture intended to represent a command. Sensors within the handheld device can record raw data, which can be processed to obtain a set of values corresponding to a set of discrete features, which is stored in a database and associated with the intended command. The process is repeated for various hand gestures representing different commands. In the recognition mode, the user can move the handheld device with a hand gesture. A computer system can compare a set of values corresponding to a set of discrete features derived from the hand gesture with the sets of values stored in the database, select a command with the closest match and displays and/or executes the command.
Abstract:
Described herein is an intelligent remote controlling device (e.g. a mobile phone). The device can include a six-axis motion sensor to accurately track three dimensional hand motions. For example, the sensors can include a three-axis accelerometer and a three-axis gyroscope. The remote control device can also include a processing unit integrated with the motion sensors in a single module. The processing unit can convert data regarding the hand motion to data regarding a cursor motion for a cursor that will be displayed on a screen of an electronic device. The processing unit can be integrated with the motion sensors in a single module (e.g. an integrated circuit chip (IC)). The processing unit can include at least two modes of functionality corresponding to different types of hand motion: a one to one mode where the cursor directly tracks the hand motion and a non-linear mode that filters data from the motion sensors to eliminate hand jitter.
Abstract:
A device disclosed herein can include a six-axis motion sensor to accurately track three dimensional hand motions. For example, the sensors can include a three-axis accelerometer and a three-axis gyroscope. The remote control device can also include a processing unit integrated with the motion sensors in a single module. The processing unit can convert data regarding the hand motion to data regarding a cursor motion for a cursor that will be displayed on a screen of an electronic device. The processing unit can be integrated with the motion sensors in a single module (e.g. an integrated circuit chip (IC)).
Abstract:
An inertial measurement system is disclosed. The inertial measurement system has an accelerometer processing unit that generates a calibrated accelerometer data. The inertial measurement system further includes a magnetometer processing unit generates a calibrated magnetometer data, and a gyroscope processing unit generates a calibrated gyroscope data. Using the calibrated accelerometer data, the calibrated magnetometer data, and the calibrated gyroscope data, the inertial measurement system generates a heading angle error indicative of the accuracy of the heading angle error.
Abstract:
An inertial measurement system is disclosed. The inertial measurement system has an accelerometer processing unit that generates a calibrated accelerometer data. The inertial measurement system further includes a magnetometer processing unit generates a calibrated magnetometer data, and a gyroscope processing unit generates a calibrated gyroscope data. Using the calibrated accelerometer data, the calibrated magnetometer data, and the calibrated gyroscope data, the inertial measurement system generates a heading angle error indicative of the accuracy of the heading angle error.
Abstract:
Described herein is an intelligent remote controlling device (e.g. a mobile phone). The device can include a six-axis motion sensor to accurately track three dimensional hand motions. For example, the sensors can include a three-axis accelerometer and a three-axis gyroscope. The remote control device can also include a processing unit integrated with the motion sensors in a single module. The processing unit can convert data regarding the hand motion to data regarding a cursor motion for a cursor that will be displayed on a screen of an electronic device. The processing unit can be integrated with the motion sensors in a single module (e.g. an integrated circuit chip (IC)). The processing unit can include at least two modes of functionality corresponding to different types of hand motion: a one to one mode where the cursor directly tracks the hand motion and a non-linear mode that filters data from the motion sensors to eliminate hand jitter.
Abstract:
Systems and methods are disclosed for determining position information for a mobile device by combining motion sensor data with acoustic sensor data.
Abstract:
An inertial measurement system is disclosed. The inertial measurement system has an accelerometer processing unit that generates a calibrated accelerometer data. The inertial measurement system further includes a magnetometer processing unit generates a calibrated magnetometer data, and a gyroscope processing unit generates a calibrated gyroscope data. Using the calibrated accelerometer data, the calibrated magnetometer data, and the calibrated gyroscope data, the inertial measurement system generates a heading angle error indicative of the accuracy of the heading angle error.
Abstract:
An inertial measurement system is disclosed. The inertial measurement system has an accelerometer processing unit that generates a calibrated accelerometer data. The inertial measurement system further includes a magnetometer processing unit generates a calibrated magnetometer data, and a gyroscope processing unit generates a calibrated gyroscope data. Using the calibrated accelerometer data, the calibrated magnetometer data, and the calibrated gyroscope data, the inertial measurement system generates a heading angle error indicative of the accuracy of the heading angle error.
Abstract:
Systems, methods, and apparatus for performing deduced reckoning navigation without a constraint relationship between orientation of a sensor platform and a direction of travel of an object are described herein. A sensor fusion component can be configured to receive data from sensors of a sensor platform coupled to a pedestrian; and generate world coordinate information based on the data. Further, a gait recognition component can be configured to record one or more walking patterns of the pedestrian in a training database; and determine whether the world coordinate information is associated with a walking pattern of the one or more walking patterns. Furthermore, a position estimation component can be configured to estimate a position of the pedestrian based on the world coordinate information if the world coordinate information is associated with the walking pattern, regardless of an orientation of the sensor platform with respect to the position of the pedestrian.