Abstract: An image capture device includes a mechanical stabilization system is used in image signal processing. The mechanical image stabilization system has an operating bandwidth and includes a motor to control an orientation of an image sensor. A processing apparatus of the image capture device determines a temperature of the motor and adjusts a cutoff frequency of the operating bandwidth based on the temperature of the motor.

Abstract: Target value detection for an unmanned aerial vehicle is described. The unmanned aerial vehicle includes a first transducer that transmits a first ultrasonic signal and receives a first ultrasonic response and a second transducer that transmits a second ultrasonic signal and receives a second ultrasonic response. The second transducer has a wider beam pattern than the first transducer. Determinations are made as to whether either or both of the first or second ultrasonic responses includes a target value within range areas associated with the respective beam patterns of the first and second transducers. A confidence value is generated based on the determinations. The target value is reflected from an object and the confidence value indicates a likelihood of a position of the unmanned aerial vehicle with respect to the object.

Abstract: The disclosed technology relates to an electronic device including a display device and an image sensor. The device may include a processor configured to cause the display device to output an illumination image in response to a command to capture one or more digital images of a scene. The processor can also be configured to cause the image sensor to receive the one or more digital images of the scene while the illumination image is displayed.

Abstract: An image capture device includes a mechanical stabilization system is used in image signal processing. The mechanical image stabilization system has an operating bandwidth and includes a motor to control an orientation of an image sensor. A processing apparatus of the image capture device determines a temperature of the motor and adjusts a cutoff frequency of the operating bandwidth based on the temperature of the motor.

Abstract: Systems and methods are disclosed for image signal processing. For example, method may include determining a sequence of orientation estimates based on sensor data from one or more motion sensors. The method may include receiving an image from the image sensor. The method may include filtering the sensor data with a pass band matching an operation bandwidth to the sequence of orientation estimates to obtain filtered data. The method may include invoking an electronic image stabilization module to correct the image based on the filtered data to obtain a stabilized image. The method may include storing, displaying, or transmitting an output image based on the stabilized image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include, based on a sequence of orientation estimates for an image sensor and an orientation setpoint, invoking a mechanical stabilization system to adjust an orientation of the image sensor toward the orientation setpoint; receiving an image from the image sensor; determining an orientation error between the orientation of the image sensor and the orientation setpoint during capture of the image; and, based on the orientation error, invoking an electronic image stabilization module to correct the image for a rotation corresponding to the orientation error to obtain a stabilized image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include determining an orientation setpoint for an image sensor; based on a sequence of orientation estimates for the image sensor and the orientation setpoint, invoking a mechanical stabilization system to adjust an orientation of the image sensor toward the orientation setpoint; receiving an image from the image sensor; determining an orientation error between the orientation of the image sensor and the orientation setpoint during capture of the image; based on the orientation error, invoking an electronic image stabilization module to correct the image for a rotation corresponding to the orientation error to obtain a stabilized image; and storing, displaying, or transmitting an output image based on the stabilized image.

Abstract: Described herein are systems and methods using a security key for an unmanned aerial vehicle. For example, some methods include during flight of an unmanned aerial vehicle, encrypting, using a public key stored by the unmanned aerial vehicle, a symmetric key that is used to encrypt media data captured using one or more sensors of the unmanned aerial vehicle to obtain encrypted media data; landing the unmanned aerial vehicle; connecting a key device to the unmanned aerial vehicle via a serial port connector of the key device and a serial port connector of the unmanned aerial vehicle; while the key device is connected to the unmanned aerial vehicle, decrypting, using a private key stored on the key device, the encrypted symmetric key, which in turn is used to decrypt a portion of the encrypted media data to obtain decrypted media data; and transmitting a portion of the decrypted media data.

Abstract: Systems and methods are disclosed for image signal processing. For example, method may include determining a sequence of orientation estimates based on sensor data from one or more motion sensors. The method may include receiving an image from the image sensor. The method may include filtering the sensor data with a pass band matching an operation bandwidth to the sequence of orientation estimates to obtain filtered data. The method may include invoking an electronic image stabilization module to correct the image based on the filtered data to obtain a stabilized image. The method may include storing, displaying, or transmitting an output image based on the stabilized image.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include determining a sequence of orientation estimates based on sensor data from one or more motion sensors; based on the sequence of orientation estimates, invoking a mechanical stabilization system to reject motions of an image sensor occurring within a first operating bandwidth with an upper cutoff frequency; receiving an image from the image sensor; based on the sequence of orientation estimates, invoking an electronic image stabilization module to correct the image for rotations of the image sensor occurring within a second operating bandwidth with a lower cutoff frequency to obtain a stabilized image, wherein the lower cutoff frequency is greater than the upper cutoff frequency; and storing, displaying, or transmitting an output image based on the stabilized image.

Abstract: The disclosed technology relates to an electronic device including a display device and an image sensor. The device may include a processor configured to cause the display device to output an illumination image in response to a command to capture one or more digital images of a scene. The processor can also be configured to cause the image sensor to receive the one or more digital images of the scene while the illumination image is displayed.

Abstract: Described herein are systems for the production, communication, routing, service, authentication, and consumption of cryptographically authenticable contextual content produced by cryptographically authenticable devices; example implementations of the architecture for a Trusted Contextual Content Device which produces Trusted Contextual Content; and example implementations of the architecture for a Trusted Drone Device which produces Trusted Contextual Content. For example, some of the methods used may include accessing a first set of sensor data from one or more sensors; receiving, a first trusted contextual content that includes a first digital signature; generating a data structure including the first trusted contextual content and data based on the first set of sensor data; signing the data structure using a signing key to generate a second trusted contextual content including a second digital signature; and storing or transmitting the second trusted contextual content.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include determining a sequence of orientation estimates based on sensor data from one or more motion sensors; based on the sequence of orientation estimates, invoking a mechanical stabilization system to reject motions of an image sensor occurring within a first operating bandwidth with an upper cutoff frequency; receiving an image from the image sensor; based on the sequence of orientation estimates, invoking an electronic image stabilization module to correct the image for rotations of the image sensor occurring within a second operating bandwidth with a lower cutoff frequency to obtain a stabilized image, wherein the lower cutoff frequency is greater than the upper cutoff frequency; and storing, displaying, or transmitting an output image based on the stabilized image.

Abstract: Described herein are systems for the production, communication, routing, service, authentication, and consumption of cryptographically authenticable contextual content produced by cryptographically authenticable devices; example implementations of the architecture for a Trusted Contextual Content Device which produces Trusted Contextual Content; and example implementations of the architecture for a Trusted Drone Device which produces Trusted Contextual Content. For example, some of the methods used may include accessing a first set of sensor data from one or more sensors; receiving, a first trusted contextual content that includes a first digital signature; generating a data structure including the first trusted contextual content and data based on the first set of sensor data; signing the data structure using a signing key to generate a second trusted contextual content including a second digital signature; and storing or transmitting the second trusted contextual content.

Abstract: Ultrasonic ranging state management for a UAV is described. A transducer transmits an ultrasonic signal and receives an ultrasonic response thereto using a gain value. A noise floor estimation mechanism determines a noise floor estimate. A state mechanism sets an ultrasonic ranging state used by the transducer to a first ultrasonic ranging state. The transducer transmits an ultrasonic signal and responsively receive an ultrasonic response to the ultrasonic signal using a gain value according to the noise floor estimate. The state mechanism processes the ultrasonic response to determine whether to determine a new noise floor estimate, adjust the gain value used by the transducer, or change the ultrasonic ranging state of the UAV to a second ultrasonic ranging state. The configurations of the first and second ultrasonic ranging states differ as to, for example, power and gain levels used by the transducer to receive ultrasonic responses.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include determining a sequence of orientation estimates based on sensor data from one or more motion sensors; based on the sequence of orientation estimates, invoking a mechanical stabilization system to reject motions of an image sensor occurring within a first operating bandwidth with an upper cutoff frequency; receiving an image from the image sensor; based on the sequence of orientation estimates, invoking an electronic image stabilization module to correct the image for rotations of the image sensor occurring within a second operating bandwidth with a lower cutoff frequency to obtain a stabilized image, wherein the lower cutoff frequency is greater than the upper cutoff frequency; and storing, displaying, or transmitting an output image based on the stabilized image.

Abstract: Ultrasonic ranging state management for a UAV is described. A transducer transmits an ultrasonic signal and receives an ultrasonic response thereto using a gain value. A noise floor estimation mechanism determines a noise floor estimate. A state mechanism sets an ultrasonic ranging state used by the transducer to a first ultrasonic ranging state. The transducer transmits an ultrasonic signal and responsively receive an ultrasonic response to the ultrasonic signal using a gain value according to the noise floor estimate. The state mechanism processes the ultrasonic response to determine whether to determine a new noise floor estimate, adjust the gain value used by the transducer, or change the ultrasonic ranging state of the UAV to a second ultrasonic ranging state. The configurations of the first and second ultrasonic ranging states differ as to, for example, power and gain levels used by the transducer to receive ultrasonic responses.

Abstract: Target value detection for an unmanned aerial vehicle is described. The unmanned aerial vehicle includes a first transducer that transmits a first ultrasonic signal and receives a first ultrasonic response and a second transducer that transmits a second ultrasonic signal and receives a second ultrasonic response. The second transducer has a wider beam pattern than the first transducer. Determinations are made as to whether either or both of the first or second ultrasonic responses includes a target value within range areas associated with the respective beam patterns of the first and second transducers. A confidence value is generated based on the determinations. The target value is reflected from an object and the confidence value indicates a likelihood of a position of the unmanned aerial vehicle with respect to the object.

Abstract: Systems and methods are disclosed for image signal processing. For example, methods may include determining a sequence of orientation estimates based on sensor data from one or more motion sensors; based on the sequence of orientation estimates, invoking a mechanical stabilization system to reject motions of an image sensor occurring within a first operating bandwidth with an upper cutoff frequency; receiving an image from the image sensor; based on the sequence of orientation estimates, invoking an electronic image stabilization module to correct the image for rotations of the image sensor occurring within a second operating bandwidth with a lower cutoff frequency to obtain a stabilized image, wherein the lower cutoff frequency is greater than the upper cutoff frequency; and storing, displaying, or transmitting an output image based on the stabilized image.

Abstract: Target value detection for an unmanned aerial vehicle is described. The unmanned aerial vehicle includes a first transducer that transmits a first ultrasonic signal and receives a first ultrasonic response and a second transducer that transmits a second ultrasonic signal and receives a second ultrasonic response. The second transducer has a wider beam pattern than the first transducer. Determinations are made as to whether either or both of the first or second ultrasonic responses includes a target value within range areas associated with the respective beam patterns of the first and second transducers. A confidence value is generated based on the determinations. The target value is reflected from an object and the confidence value indicates a likelihood of a position of the unmanned aerial vehicle with respect to the object.